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graphpipe | img src docs assets logo png width 500 style display block width 500px margin auto margin bottom 3em graphpipe machine learning model deployment made simple what is it graphpipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework specific model implementations the existing solutions for model serving are inconsistent and or inefficient there is no consistent protocol for communicating with these model servers so it is often necessary to build custom clients for each workload graphpipe solves these problems by standardizing on an efficient communication protocol and providing simple model servers for the major ml frameworks we hope that open sourcing graphpipe makes the model serving landscape a friendlier place see more about why we built it here https oracle github io graphpipe guide user guide overview or browse the rest of the documentation https oracle github io graphpipe features a minimalist machine learning transport specification based on flatbuffers simple efficient reference model servers for tensorflow caffe2 and onnx efficient client implementations in go python and java flatbuffers https google github io flatbuffers tensorflow https www tensorflow org caffe2 https caffe2 ai onnx https onnx ai what is in this repo this repo contains documentation as well as the flatubuffer definition files that are used by other language specific repos if you are looking for graphpipe clients servers and example code check out our other graphpipe repos https github com oracle graphpipe go the graphpipe go client library https github com oracle graphpipe go tree master cmd graphpipe tf go implementation of a graphpipe tensorflow model server https github com oracle graphpipe go tree master cmd graphpipe onnx a go implementation a graphpipe onnx caffe2 model server https github com oracle graphpipe py the graphpipe client library for python https github com oracle graphpipe tf py a python implementation of a remote operation client for tensorflow as well as some example server implementations building flatbuffer definitions if you ve got flatc installed you can just make all but if you don t want to install it you can export use docker 1 and then make all remember make needs vars exported not just on the command line where you run make this will produce the go c and python libraries which can then be copied into their projects graphpipe go graphpipe tf py and graphpipe py respectively contributing all of the graphpipe projects are open source to find out how to contribute see contributing md contributing md you can also chat us up on our slack channel https join slack com t graphpipe shared invite enqtnde4mtuyodk2nzqzltuwodlkzdriyti4nme1ota5nzrmnjk5mgziy2m0zdriyznimtq0zmixodyzzjy2nzrmnzm4nti0ogvlzgyzzta | ai |
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learning_to_see | learning to see challenge graphics finger counting demo gif about this repository supports the youtube series learning to see https www youtube com watch v i8d90dkclhi list pliahhy2ibx9ihlasve8bkns2xg8ahy6iv we ll take a bottom up appraoch to machine learning for computer vision and tackle one problem counting the number of fingers in an image from a leap motion https www leapmotion com infared camera lectures order notebook slides topic required viewing before additional reading notes 1 rules https github com unccv learning to see blob master notebooks 1 rules ipynb let s try a rules based approach to real cv problem lts part 1 https www youtube com watch v i8d90dkclhi list pliahhy2ibx9ihlasve8bkns2xg8ahy6iv intro to programming challenge https github com unccv learning to see blob master challenge challenge instructions ipynb 2 machine learning https github com unccv learning to see blob master notebooks 2 machine 20learning ipynb can we learn a better way from data lts part 2 3 https www youtube com watch v 2zhqkd1qkfw index 2 list pliahhy2ibx9ihlasve8bkns2xg8ahy6iv 3 generalization https github com unccv learning to see blob master notebooks 3 generalization 20and 20legos ipynb how do we know if our models are actually working lts part 4 5 https www youtube com watch v sarvw ivwgc index 4 list pliahhy2ibx9ihlasve8bkns2xg8ahy6iv surely you re joking mr feynman https www amazon com surely youre joking mr feynman ebook dp b003v1wxku ref sr 1 1 ie utf8 qid 1530909477 sr 8 1 keywords surely you 27re joking mr feynman 4 learning from data https github com unccv learning to see blob master slides learning from data pptx but how do we really know that our models are working lts part 6 7 https www youtube com watch v gufqykmkdpw index 6 list pliahhy2ibx9ihlasve8bkns2xg8ahy6iv caltec learning from data lecture 2 https www youtube com watch v meg35rdd7ra hd 1 5 simple rules https github com unccv learning to see blob master slides simple rules pptx why should we prefer simple rules lts part 8 9 https www youtube com watch v uvwwyzmfocg caltec learning from data lecture 2 https www youtube com watch v meg35rdd7ra hd 1 6 decision trees https github com unccv learning to see blob master slides decision trees pptx how do we actually find good rules lts part 10 15 https www youtube com watch v 6cvpj9dmyto hackerdashery p vs np https www youtube com watch v yx40hbahx3s setup the python 3 anaconda distribution https www anaconda com download is the easiest way to get going with the notebooks and code presented here optional you may want to create a virtual environment for this repository conda create n cv python 3 source activate cv you ll need to install the jupyter notebook to run the notebooks conda install jupyter you may also want to install nb conda enables some nice things like change virtual environments within the notebook conda install nb conda this repository requires the installation of a few extra packages you can install them all at once with pip install r requirements txt optional jupyterthemes https github com dunovank jupyter themes can be nice when presenting notebooks as it offers some cleaner visual themes than the stock notebook and makes it easy to adjust the default font size for code markdown etc you can install with pip pip install jupyterthemes recommend jupyter them for presenting these notebook type into terminal before launching notebook jt t grade3 cellw 90 fs 20 tfs 20 ofs 20 dfs 20 recommend jupyter them for viewing these notebook type into terminal before launching notebook jt t grade3 cellw 90 fs 14 tfs 14 ofs 14 dfs 14 notes launching the jupyter notebooks to properly view the images and animations please launch your jupyter notebook from the root directory of this repository graphviz on windows windows users may need to install graphviz separetely if you are getting graphviz s executables not found https stackoverflow com questions 18438997 why is pydot unable to find graphvizs executables in windows 8 exception in notebook 4 1 download graphviz msi https graphviz gitlab io pages download download windows html 2 add c program files x86 graphviz2 34 bin to your path variable 3 stop exit your current python environment ide and start again | ai |
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calendays | calendays react web app web application used for shared event planning uses firebase for user authentication and storing user data events networks profile once authenticated and verified users can create events to be displayed on their calendar users can also create named networks which consist of groups of two or more users see the backend server here https github com justinkonecny webserver golang project breakdown screenshots this folder contains a series of screenshots taken throughout the development of the application src index css css for the index page index tsx typescript for the index page initializes and configures firebase for the application renders the main app component in a browserrouter mainroutes tsx configures the routes for the application https calendays jkonecny com login login screen https calendays jkonecny com home home shared calendar https calendays jkonecny com user home user calendar user profile https calendays jkonecny com notifications home event notifications https calendays jkonecny com reset reset password reset src components calendar calendar tsx component that given user events renders the main calendar for the current week of the month additional weeks are rendered as the user changes the displayed week calendarday js component used by calendar represents one day in week one calendar column renders given list of events at their specified times newevent tsx component to allow the user to create a new event handles updating the firebase store with newly created event src components common dropdowndate tsx dropdown component used for selecting from a list of date dropdowntime tsx dropdownnetwork tsx inputfield tsx src components main app tsx constants ts home tsx login tsx navbar tsx notifications tsx reset tsx user tsx src components networks group tsx networks tsx newnetwork tsx src components profile profile tsx src data networkevent ts networkgroup ts networkuser ts pages ts userprofile ts user interface login screen alt text screenshots readme login png login landing screen alt text screenshots readme landing png landing event creation screen alt text screenshots readme event create png event creation network creation screen alt text screenshots readme network create png event creation | server |
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atsea-sample-shop-app | atsea store png atsea shop demonstration application the atsea shop is a demonstration application comprised of java rest application written using spring boot a database for product inventory customer data and orders a react shopping cart a nginx reverse proxy implementing https a payment gateway to simulate certificate management requirements this example uses features in docker 17 05 ce edge install this version to run the example building and running the atsea shop secrets this application uses docker secrets to secure the application components the reverse proxy requires creating a certificate that is stored as a secret and the payment also requires a password stored as a secret to create a certificate and add as a secret mkdir certs openssl req newkey rsa 4096 nodes sha256 keyout certs domain key x509 days 365 out certs domain crt docker secret create revprox cert certs domain crt docker secret create revprox key certs domain key docker secret create postgres password certs domain key to create a secret for staging the payment gateway echo staging docker secret create staging token run as an application to run the atsea shop as an application docker compose up build deploy to a swarm if you need to create a swarm docker swarm init docker stack deploy c docker stack yml atsea a simplified development environment this compose file creates a simplified development environment consisting of only the application server and the database docker compose file docker compose dev yml up build the atsea shop the url for the content is http localhost 8080 rest api documentation for rest calls rest api rest md | java spring-boot react docker swarm-mode | front_end |
jeevan-rakht | github issues https img shields io github issues udacityfrontendscholarship jeevan rakht svg https github com udacityfrontendscholarship jeevan rakht issues github pull requests https img shields io github issues pr udacityfrontendscholarship jeevan rakht svg https github com udacityfrontendscholarship jeevan rakht pulls github forks https img shields io github forks udacityfrontendscholarship jeevan rakht svg style social label fork https github com udacityfrontendscholarship jeevan rakht network github stars https img shields io github stars udacityfrontendscholarship jeevan rakht svg style social label stars https github com udacityfrontendscholarship jeevan rakht stargazers github watchers https img shields io github watchers udacityfrontendscholarship jeevan rakht svg style social label watch https github com udacityfrontendscholarship jeevan rakht watchers github contributors https img shields io github contributors udacityfrontendscholarship jeevan rakht svg https github com udacityfrontendscholarship jeevan rakht graphs contributors googleudacity jeevanrakht jeevanrakht is a virtual blood bank web app that aims at providing mechanism for people in need to directly talk to willing donors and also find out blood availability in nearby blood banks on this platform people willing to donate blood can sign up with details of their blood groups location also there ll be accounts of blood banks with details like number of packages of blood available and blood group location of blood bank to filter out nearest blood banks you can find the project s wireframe below which depicts the basic flow of our web application mods imran khan strongsoda vidit kothari viditkothari shashank kumar mcashashankkumar sujan patel sujan patel utkarsh gupta utkarsh2102 gaurav singh gauravsinghaec soumya ranjan behera soumya44 hardiki devre hardiki special thanks to akshit udacity please refer to this paper https paper dropbox com doc jeevanrakht webd project 5vccfmnq3exrip5q20lpp here it ll give you an insight of the project s working in case of any doubts regarding the same do feel free to contact any mod or co mod project wireframe wireframe flow https user images githubusercontent com 15084301 38657424 c22747d2 3e3d 11e8 9447 7862553d7142 jpg getting started jeevanrakht has separate home page for website and web application this project consists of two part like all web application frontend part html css jquery and bootstrap4 backend part node js with express js and mongodb color palette color palette https raw githubusercontent com udacityfrontendscholarship jeevan rakht master public assets color 20palette jpg homepage mockup jeevanrakht pdf https github com udacityfrontendscholarship jeevan rakht files 1907369 jeevanrakht pdf web application page https jeevanrakht herokuapp com website page https jeevanrakht herokuapp com index html learn about folder structure check faq for more info on folder structure note the folder structure may changes i e we may include exclude some folders files as project progresses but the overall sructure will remain as presented below backend part node js express js with mongodb bin application code listening for http requests config db connection url oauth2 secrets etc to be used in application db mongodb driver code to be used in application models mongodb collections schema routes apllication code for handling different ui routes e g login users etc views apllication related htmls files related to application routes controllers methods to interact with db and reflects the data on views utils common utility functions used in application app js application driver code frontend part public index html homepage for our website public assets this will have scss css js images css app css css for our application main css css for our website js app js js for our application main js js for website images put your images here optimized images we will create optimized images using grunt image magick to optimize site app performance scss we are not using it as most people are not familier with scss gulpfile js this is a task runner to launch app and monitor for file scss css js changes and reloads the browser common to both frontend and backend views this will have htmls for our app the htmls are with hjs extension auth this module will have htmls related to authentication and authorization e g login signup etc main this module will have htmls related to main blocks of app e g locate and donate profile this module will have htmls related to user profiles partials this module will have common htmls blocks which will be used in all other htmls e g head header footer etc app hjs this is the home page of our app 404 hjs html for page not found package json below is used to generate optimized image gruntfile js br getting started with grunt https gruntjs com getting started below is used to deploy web app on heroku procfile procfile windows br learn about building deploying and managing your apps on heroku https devcenter heroku com generic web stack diagram image https user images githubusercontent com 15084301 40181948 eb29ca52 5a07 11e8 8bac 3cb0506ccfe6 png br know more about web stack https dzone com articles why full stack development is too good for you in how to launch the app locally step1 fork the project repo and clone it in your local directory note you can directly update the frontend components inside public directory but we have used gulp to automate the process you need not to refresh the page after each change or go to codepen to check your changes you made in scss or html or js files just run gulp and have fun step2 download and install node latest stable version npm comes along with node br node https nodejs org en e g v 8 11 br what is npm https www npmjs com verify with below command node v npm v with node 10 x version i see people struggling to start the application using npm start command therefore i request everyone to go for stable version of node i e 8 11 make sure you run all your commands fron inside cloned jeevan rakht folder step3 install the npm modules from the package json npm install this command installs all the node related packages required to run the app locally in node modules folder you can see this folder inside jeevan rakth folder after running npm install step4 launch the application using below command below command will run gulpfile js and start the static website frontend npm install g gulp gulp the application will be running at http localhost 3000 url what is gulp https gulpjs com gulp run https user images githubusercontent com 15084301 38658055 110a4996 3e41 11e8 9c28 9324e87cd008 jpg or below command will start as full web application backend frontend npm install g nodemon npm start the application will be running at http localhost 3000 if not then please check if you have set any default port in your environment path variable i e http localhost your env port variable node run https user images githubusercontent com 15084301 38658058 17bea426 3e41 11e8 8dd6 9009ba81fcc3 jpg if you get an node sass module error while running npm start saying app crashed then make sure your node version is 8 11 not 10 x and if the issue still persists then run the command as shown in below image image https user images githubusercontent com 15084301 39688089 b99528fe 51ee 11e8 9ee2 35ec7a46ccf2 png step5 no more steps now you don t need to repeat above steps always to run the app rather its one time task but if you clone the project in new location then again you need to repeat step 3 only connect with co mods if you stuck anywhere restfull apis for jeevanrakht web application jeevanrakht rest apis pdf https github com udacityfrontendscholarship jeevan rakht files 1911725 jeevanrakht rest apis pdf contributing guidelines please refer to this contributing guide https github com udacityfrontendscholarship jeevan rakht blob master contributing md to know more about general guidelines creatig issues pull requests git commits etc faq i can see many changes in the parent project repo how may i sync my github repo with parent repo without losing my changes which i am currently working on in my local sync forked repo with parent repo docx https github com udacityfrontendscholarship jeevan rakht files 1917880 sync forked repo with parent repo docx how can i get the link to add in prs to show my changes you can share the github pages link or heroku link where reviewer can go can see you changes live which will help them to take a call on your pr efficiently br know more about github pages https guides github com features pages br deploying applications with heroku https in udacity com course deploying applications with heroku ud272 where is the homepage for the jeevanrakht jeevanrakht has separate home page for website and web application views app hjs is the home page for web application whereas public index html is the static page for our website where to start i am not getting where are the html files for the website and web application all html files for the website is inside public folder and all the html files for web application is inside views folder under different modules i don t see any html files in views folder all the htmls are there with hjs extension under views feel free to open and edit it like you do any other html files there are many subfolders inside views i can see only app hjs and 404 hjs files we have divided and modularized our folder structure based on the functionalities to manage the files efficiently otherwise it will be very chaotic once your project grows below are the main modules in our application auth it has all files related to authentication e g login signup forgot pw pages etc main it has main components of application e g locate and donate related pages profile it contains pages corresponding to user profiles update email mobile etc others all other random files are kept here what is 404 hjs file used for 404 hjs is default page to be shown to user if he she visits any url wrong path which is not the part of jeevanrakth application contributors you will find yourself in contributors list once your pr is approved and merged into jeevan rakht rapo here you goes to find all the contributors image https user images githubusercontent com 15084301 40287668 a3cb2df0 5ccc 11e8 8c23 13788e527c9c png working repo site repo https github com udacityfrontendscholarship jeevan rakht site https jeevanrakht herokuapp com index html app https jeevanrakht herokuapp com style guide this style guide acts as the official guide to follow in your projects udacity evaluators will use this guide to grade your projects there are many opinions on the ideal style in the world of front end web development therefore in order to reduce the confusion on what style students should follow during the course of their projects we urge all students to refer to this style guide https udacity github io frontend nanodegree styleguide for their projects | front_end |
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westerfield | westerfield development server run nx serve cloud for a dev server navigate to http localhost 4200 the app will automatically reload if you change any of the source files codespace port forwarding run nx serve cloud host 0 0 0 0 if codespace doesn t automatically forward the application port understand this workspace this workspace is managed with nx workspace https nx app graphing run nx graph to see a diagram of the dependencies of the projects remote caching run npx nx connect to nx cloud to enable remote caching https nx app and make ci faster further help visit the nx documentation https nx dev to learn more | cloud |
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app-icon-generator | mobile app icon generator for mac os x mac os x app to generate multiple size for app icon support ios 7 or newer iphone ipad app newest android studio work on mac os x 10 9 or newer also support el capitan download latest version https github com laptrinhcomvn ios app icon generator releases v2 1 updated to support macos sierra now support for xcode 8 ios 10 icon set v2 0 support mac os x 10 11 el capitan support android app icon v1 0 ios 7 or newer work on mac os x 10 9 10 10 screenshots alt text http 3 bp blogspot com wwghsow55i8 vhtexasqqvi aaaaaaaaad0 jnoihjsvv14 s320 screen 2bshot 2b2015 10 07 2bat 2b3 58 05 2bpm png app main screen alt text http 1 bp blogspot com zr5loabbeek vvqvkoyff9i aaaaaaaaare 79hjajz 6fw s320 screen 2bshot 2b2015 05 19 2bat 2b10 33 30 2bam png generated icon set result | icon-generator | front_end |
bigchaindb | copyright 2020 interplanetary database association e v bigchaindb and ipdb software contributors spdx license identifier apache 2 0 and cc by 4 0 code is apache 2 0 and docs are cc by 4 0 there is no shield to get the latest version including pre release versions from pypi so show the latest github release instead codecov branch https img shields io codecov c github bigchaindb bigchaindb master svg https codecov io github bigchaindb bigchaindb branch master latest release https img shields io github release bigchaindb bigchaindb all svg https github com bigchaindb bigchaindb releases status on pypi https img shields io pypi status bigchaindb svg https pypi org project bigchaindb travis branch https img shields io travis bigchaindb bigchaindb master svg https travis ci com bigchaindb bigchaindb documentation status https readthedocs org projects bigchaindb server badge version latest https docs bigchaindb com projects server en latest join the chat at https gitter im bigchaindb bigchaindb https badges gitter im bigchaindb bigchaindb svg https gitter im bigchaindb bigchaindb utm source badge utm medium badge utm campaign pr badge utm content badge bigchaindb server bigchaindb is the blockchain database this repository is for bigchaindb server the basics try the quickstart https docs bigchaindb com projects server en latest quickstart html read the bigchaindb 2 0 whitepaper https www bigchaindb com whitepaper check out the hitchiker s guide to bigchaindb https www bigchaindb com developers guide run and test bigchaindb server from the master branch running and testing the latest version of bigchaindb server is easy make sure you have a recent version of docker compose https docs docker com compose install installed when you are ready fire up a terminal and run text git clone https github com bigchaindb bigchaindb git cd bigchaindb make run bigchaindb should be reachable now on http localhost 9984 there are also other commands you can execute make start run bigchaindb from source and daemonize it stop it with make stop make stop stop bigchaindb make logs attach to the logs make test run all unit and acceptance tests make test unit watch run all tests and wait every time you change code tests will be run again make cov check code coverage and open the result in the browser make doc generate html documentation and open it in the browser make clean remove all build test coverage and python artifacts make reset stop and remove all containers warning you will lose all data stored in bigchaindb to view all commands available run make links for everyone bigchaindb com https www bigchaindb com the main bigchaindb website including newsletter signup roadmap https github com bigchaindb org blob master roadmap md blog https medium com the bigchaindb blog twitter https twitter com bigchaindb links for developers all bigchaindb documentation https docs bigchaindb com en latest bigchaindb server documentation https docs bigchaindb com projects server en latest index html contributing md github contributing md how to contribute community guidelines code of conduct md open issues https github com bigchaindb bigchaindb issues open pull requests https github com bigchaindb bigchaindb pulls gitter chatroom https gitter im bigchaindb bigchaindb legal licenses licenses md open source open content imprint https www bigchaindb com imprint contact us https www bigchaindb com contact | blockchain database json python bigchaindb mongodb bft decentralized | blockchain |
GALLM | p align center width 100 a href https app yunhan ai com target blank img src logo png alt galaxy ai style width 25 min width 300px display block margin auto a p gallm galaxy ai large language model english https github com galaxy ai gallm edit main readme md https github com galaxy ai gallm edit main readme zn md gallm is an open source bilingual dialogue language model that supports both chinese and english based on llama https arxiv org abs 2302 13971v1 architecture gallm optimized for chinese q a and dialogue based on llama after about 2t chinese identifier training supplemented by technologies supervised fine tuning feedback self service and human feedback reinforcement learning gallm1 0 we are able to generate responses that align well with human preferences please visit our at official website https www yunhan ai com for more details what s new open source part of the data set april 24 2023 gallm2 0 publish gallm2 0 it is a large scale language model based on deep learning technology with parameters in the tens of billions compared to hundreds of millions in gallm1 0 this model uses pre training techniques like bert and incorporates techniques components from various language models and knowledge bases enabling it to achieve strong performance on semantic understanding information extraction and text classification and other aspects gallm2 0 has an optimized model architecture and training algorithm leading to further performance gains march 9 2023 galaxy ai application matrix publish img src help jpg alt galaxy ai style width 20 min width 100px margin right 30px img src counselor jpg alt galaxy ai style width 20 min width 200px margin right 10px img src advertorial jpg alt galaxy ai style width 20 min width 300px margin right 10px img src painting jpg alt galaxy ai style width 20 min width 400px margin right 10px march 8 2023 gallm1 0 publish november 16 2022 galaxy ai painting mini program publish october 13 2022 galaxy ai painting platform publish march 16 2022 team establishment llama paper https arxiv org abs 2302 13971v1 self instruct paper https arxiv org abs 2212 10560 data generation https github com lianjiatech belle and https guanaco model github io the first work https github com tatsu lab stanford alpaca gallm2 0 this upgraded model gallm2 0 is now available on galaxy ai ai plus platform users can follow the wechat official account ai or visit our website ai plus platform https app yunhan ai com there users can understand and experience the powerful capabilities of gallm2 0 the ai plus platform also offers various ai tools such as those for new media writing e commerce education and workplace these tools can substantially improve productivity and efficiency | ai |
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system-props | system props responsive theme based style props for building design systems with react https system props com version npm size mit license license version https flat badgen net npm v system props npm https npmjs com package system props size https flat badgen net bundlephobia minzip system props license https flat badgen net badge license mit blue sh yarn add system props features functions almost identically to styled system but adds the following features written in typescript chakra s pseudobox inspired pseudo selector props access the theme object at any time by using the function syntax supports common themed shorthand properties like border margin padding and box shadow strict mode allow only values that are present in the theme visually distinguish theme values by prefixing system prop values with quick start see the example project in this repo for a more complete example tsx import createsystem color space from system props import styled themeprovider from styled components const theme space 0px 4px 8px 16px 32px colors blue100 lightblue blue200 blue etc const system createsystem strict default false pseudoselectors default hover hover etc const box styled div system color space const app return themeprovider theme theme box bg blue500 margin 1 2 3 4 border 1px solid blue200 borderbottom theme 3px dotted theme colors blue200 hover bg blue700 themeprovider credits many of the concepts here come from so many great existing open source projects and they deserve a shout out styled system https github com styled system styled system duh chakra ui https chakra ui com and the pseudobox stitches https github com modulz stitches sprout s system props documentation https seeds sproutsocial com components system props | styled-system css-in-js design-system style-props tokens theming design-tokens styled-components emotion css react typescript | os |
private_watermark | a private watermark for large language models conda environment python 3 9 pytorch others pip install r requirements txt four steps step 1 generate data for training watermark generator we need to train the watermark generator network in order to divide the red green list evenly approximately half green and half red shell python generate data py bit number 16 window size 3 sample number 2000 output file train generator data train generator data jsonl the value of bit number depends on the llm you choose to use for example gpt2 has a vocabulary size of 50 257 2 15 1 50257 2 16 1 and therefore we let bit number 16 step 2 train watermark generator shell python model key py data dir train generator data train generator data jsonl bit number 16 model dir model window size 3 layers 5 step 3 generate training and testing data for watermark detector generate training data python watermark generate and save train data args train num samples args output dir llm is not used in this step we randomly sample 10 000 token id sequences of length 200 and calculate z score using the watermark generator judging whether each token is green or not generate testing data python watermark generate and save test data args llm name args dataset name args output dir args sampling temp args max new tokens llm is used in this step we use the validation set of c4 and dbpedia for experiments you can find them in original data text 1 500 in c4 and text 1 500 in dbpedia are selected to generate testing data with prompt length of 30 and new generated text length of 200 shell python watermark model py bit number 16 train num samples 10000 dataset name c4 llm name gpt2 output dir data model dir model window size 3 layers 5 use sampling true sampling temp 0 7 n beams 0 max new tokens 200 delta 2 0 step 4 train and test our private watermark detector shell python detector py llm name gpt2 bit 16 window size 3 input data model file model sub net pt output model dir model layers 5 z value 4 model and data of main experiments in directory experiments we provide the trained watermark generator model of main experiments together with the training data and testing data that are already generated for each experiment setting llm gpt2 opt 1 3b llama 7b top k beam search 500 sentences of watermarked text tagged as 1 and 500 sentences of the corresponding unwatermarked text natural corpus tagged as 0 are provided in test data jsonl you can train and test our private watermark detector simply by 1 changing line 122 in detector py into train data prepare data os path join experiments train and test data train data jsonl train or test train bit bit number z value z value llm name llm name 2 running shell python detector py llm name gpt2 bit 16 window size 5 input experiments train and test data gpt2 c4 topk model file experiments generator model sub net pt output model dir experiments detector model gpt2 c4 topk layers 5 z value 1 tips you may need to change llm tokenizer path in detector py line 69 72 75 you may need to set appropriate z value in different experiment settings | ai |
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shifting-attention-to-relevance | shifting attention to relevance towards the uncertainty estimation of large language models arxiv https arxiv org abs 2307 01379 code is coming | ai |
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Deep-Learning-Experiments-implemented-using-Google-Colab | colab fastai colab compatible fastai notebooks for mainly nlp computer vision and recommender systems fastai describes the work in 4 forms 1 tabular we are provided with a tabular data and we need to do regression classification jeremy believes in using deep learning wherever we can and for the situation where we are not sure about deep learning implement random forests as taught in ml series find more related works at https github com navneetkrc colab fastai tree master tabular 2 nlp here we have nlp related tasks and we are using ulmfit models as our embeddings and find great results this is based on language models they are fine tuned to our dataset to include dataset specific words and sentence structure the language model training is converted into semisupervised task by trying to predict the next word using transfer learning starting from wikitext model and finetuning for our dataset and we implement our text classifier from scratch based on the newly finetuned word embeddings find more related work at https github com navneetkrc colab fastai tree master nlp 3 cv image datasets here we have a lot of images as our data and we want to implement image classifiers usually here we use transfer learning and we use one of the imagenet pretrained model and finetune it as well for our dataset and the classifier part gives probability distribution for the classes that we want for prediction find such datasets and work at https github com navneetkrc colab fastai tree master image 20datasets 4 recommender systems here we implement recommender systems based on user and item embeddings and it turns out that by using these simple approach we are able to get good results for recommender systems find more related work at https github com navneetkrc colab fastai tree master recommender 20systems major highlights of the projects work done computer vision projects https github com navneetkrc colab fastai blob master image 20datasets intel image classification3 ipynb this is a google colab notebook on the intel image classification hosted on the analytics vidhya in this there are 17034 images in train and 7301 images in test data the categories of natural scenes and their corresponding labels in the dataset are as follows buildings 0 forest 1 glacier 2 mountain 3 sea 4 street 5 reached 95 accuracy on the validation data in order to classifiy with more accuracy need to handle the mislabelled data that we provide as part of training data for now it is not done as it is more time taking https github com navneetkrc colab fastai blob master image 20datasets food image ipynb this is google colab notebook for the food data hackathon hosted by rakuten in which i got good accuracy almost top 10 but was not able to submit the test results after the added documentation in the fastai library testing for the test data and adding for that has become more convenient and same has been applied in the intel image classification challenge as well https github com navneetkrc colab fastai blob master image 20datasets kyc multimodels ipynb this google colab notebook is for kyc verification of id documents and classify them correctly as aadhar pancard dl passport voterid data is scraped from google and by only using 30 images for each classes i was getting good results this can be extended to any number of documents just need to add the corresponding data nlp based projects newsgroup dataset https github com navneetkrc colab fastai blob master nlp newsgroup ulmfit fastai text classification ipynb is the first project in nlp in this we used a lot of sklearn data handling as well and suggest this to be your first dataset as well to check your understanding this is the example i used in my meetup presentation medicinal review rating prediction https github com navneetkrc colab fastai blob master nlp medicine review ulmfit fastai short ipynb this is a google colab notebook on the medicinal dataset provided on kaggle kaggle datasets download d jessicali9530 kuc hackathon winter 2018 in this i created a subtask of getting the reviews and the rating i have created a classifier model in which i predict the rating that a user would give based only on text next iterations i will add more columns and see how adding those columns will affect the results av funny jokes https github com navneetkrc colab fastai blob master nlp av funny jokes ipynb is a dataset provided by analytics vidhya where they provide text dataset of jokes and then based on different users and joke we predict what rating would a new user give to the joke fastai movie review https github com navneetkrc colab fastai blob master nlp fast ai movie review ipynb this is just the colab implementation of the lecture in fastaiv3 for the nlp example yelp movie review using fastai v1 https github com navneetkrc colab fastai blob master nlp yelp review ulmfit fastai short ipynb similar to the fastai dataset of movie review this one is also there very big dataset and that is the only thing that restricts us for now in training in the google colab envirionment rest is ready and well documented recommender systems movielens recommender systems based on user and movie embeddings using only pytorch https github com navneetkrc colab fastai blob master recommender 20systems emb based recsys pytorch movielens emb pytorch ipynb i will keep adding more projects and try out some of the projects based on the fastai v3 part 2 | fastai nlp colab-notebook colab-fastai computer-vision-datasets jokes kaggle collab movie-reviews recommender-systems google-colab-notebook computer-vision transfer-learning classifier smote embeddings | ai |
web | squash a squarish bug spray an open source project from square http github com square squash is a collection of tools that help engineers find and kill bugs in their code by automatically collecting collating and analyzing run time exceptions squash consists of the following components client libraries client libraries for different systems ruby ruby on rails cocoa with objective c etc catch and record errors when they occur then send them to the api endpoint client libraries can be found under the squaresquash organization https github com squaresquash front end this website displays bug information and helps the engineer find the root cause for a bug and fix it it also lets engineers manage assign and comment on bugs as well as view statistics about the bug api endpoints these routes part of the front end app receive exception notifications from the client libraries and process them this project is the front end and the api pull requests are more than welcome please check out contributing md file contributing html for details how to install to get started run the bin setup file this script will ask you a series of questions and generate a preliminary configuration for your site install when the script is completed you can run git status to see what files it changed and refine your configuration from there once the script is complete squash should run for most typical development environments simply run rails s and visit the site in your web browser you should be able to start using it immediately you can also verify correctness by running rspec spec configuring and deploying the production instance is entirely up to you and your particular production environment additional configuration options can be found in the following locations config application rb config environments rb config environments yml if you don t see what you re looking for in any of those files you ll probably have to change the code to make it work don t be afraid the code is thoroughly documented and should hopefully be very accessible requirements squash requires the following ruby 1 9 2 or newer jruby with 1 9 is supported multithreading support see the next section postgresql 9 1 or newer the bundler gem git 1 7 or newer notes on some of the gem and library choices why do you specifically require postgresql squash uses a lot of postgresql specific features to make efficient use of the database and maintain referential integrity such as foreign key constraints triggered cached counters check constraints and semantic indexes for text based search if postgresql is out of the question some of these features can be ported to other rdbmses simply edit the initialschema migration and update the sql as necessary if portability is required a lot of these features can be reimplemented in the rails layer e g cached counters at the risk of degraded referential integrity if you are reimplementing the cached counters in ruby be sure to modify the config initializers active record rb file as appropriate if you do successfully port squash to another rdbms let me know i d be happy to take your changes why do you bundle an edge version of rails the 3 2 stable branch of ruby on rails includes some changes to active record that are required by squash s multithreaded concurrency model see next question in particular that version of active record includes crucial changes to the connection pool and connection reopening logic if you set the background runner option in the concurrency yml file to something other than multithread the gemfile will automatically drop rails back down to the latest release version why don t you use my favorite backgrounding library squash was originally built for square which runs all its services on jruby using threads is very efficient in jruby and avoids the overhead of having to deploy both a website and workers if you are running squash in a non thread safe or multithreading unfriendly environment you can use sidekiq or resque instead if you want to use some other backgrounding library you can easily write your own adapter all threaded code is invoked using backgroundrunner run which then uses the settings in the concurrency yml configoro file to invoke the correct module under lib background runner the default is to use backgroundrunner multithread which uses the multithread module to execute the task in its own thread you can edit the yaml file and switch the background runner to resque or implement your own backgroundrunner module see the backgroundrunner documentation for more details if you do this successfully and wish to save future squash users the effort feel free to turn your changes into a pull request why aren t you using redcarpet as mentioned above squash was originally built to run under jruby redcarpet has compiled c extensions kramdown is pure ruby why do you require a recent version of git squash uses the git clone mirror command to create local mirrors of client projects git repositories why don t you have integration tests or acceptance tests to be 100 honest lack of familiarity on these things in ruby rails happy for any help people want to extend towards this goal why are you using erector i like erector documentation comprehensive documentation is written in yard and markdown formatted comments throughout the source to view this documentation as an html site run rake yard coffeescript libraries are documented using the yard format as well but yard does not as yet recognize them as documentable files a codoopts file is included in case you wish to use codo https github com netzpirat codo to generate the coffeescript docs but as of now codo does not recognize the erb files and does not use the full set of markdown syntax features used in the documentation project overview views this is a pretty typical rails website save for the views which are written using erector the views forgo the traditional rails concepts of partials and templates in favor of analogous oop concepts more familiar to software developers methods and inheritance all views inherit from an abstract erector widget which provides layout and all views have their content split into multiple private methods in addition to the usual helpers in app helpers there are view mixins under app views additions that simplify view coding embedded code snippets are all rendered using the commitscontroller context action this action loads the appropriate file and revision from the git repository and returns a snippet plus the name of the syntaxhighlighter brush to use the brush is determined from the file name extension the mapping can be found in data brushes yml this view behavior is provided from a javascript library file in lib assets javascripts there are many similar helper classes in there they are documented but the documentation is not recognized by yard and so is not included in this documentation set javascript files are organized into four possible locations third party javascript libraries are in vendor assets javascripts and loaded in the application js manifest javascript modules or helpers that are not specific to a particular page or site area are in lib assets javascripts and also loaded in application js javascript modules or helpers specific to a particular area of the site are in app assets javascripts and also loaded in application js small javascript snippets glue code or other code intended to add dynamic behavior to a specific page is in a js file named the same as and placed alongside the html rb view file for example if app views projects new html rb needed a bit of js glue code it would be placed in app views projects new js this code is placed in a script tag at the end of the view by the views layouts application inline javascript method css files are similarly organized third party css files are in vendor assets stylesheets and loaded in the application css manifest css styles or helpers global to the entire website are in lib assets stylesheets and also loaded in application css css styles specific to a single page or a related group of pages are placed in app assets stylesheets and also loaded in application css each body tag is given a class name equal to the controller name and an id equal to the controller and action name separated with a dash for instance the projects new action s body would be body class projects id projects new controllers for information about requests and responses see applicationcontroller models models make extensive use of advanced postgresql features for efficiency and convenience cached counters are updated using triggers and rules foreign key constraints and hooks are enforced at the database level and validations are backed up by corresponding check triggers this helps ensure referential and data integrity even in situations where rails fails or outside of the rails stack see the various migrations to learn more about the triggers rules and constraints being used observers are used for more high level triggers such as creating event events at the appropriate times or sending emails see the classes in app models observers for more models also use the hasmetadatacolumn gem to reduce their width and incorporate schemaless data most models have a json formatted metadata column to which new information can be added or removed without having to create new migrations tasks various rake tasks are available under lib tasks these include tasks for pruning and maintaining the database development tasks and configuring the workers workers workers are found in the lib workers directory along with occurrencesworker which stores and categorizes occurrences there are other workers for managing deploys and other minor tasks these workers are run asynchronously using multithread mailers notification mails are sent by the notificationmailer it and any other mailers live in app mailers notificationmailer conditionally delivers emails an email will only be delivered if all of the following conditions are met the project has a mailing list email configured for the critical bugs and all bugs mailing lists the environment s sends emails attribute is true and the user has enabled receipt of that category of emails typically specified in the membership authentication and authorization authentication is done using either password verification or ldap see authenticationhelpers and related controller mixins as well as the model mixins under app models additions for more information there are four permissions levels that a user can have specific to an individual project non members do not have a membership record with a project they can view bugs and occurrences view the project s api key view the list of other project members watch bugs and comment on bugs members can do everything non members can do and can also assign bugs be assigned bugs and modify delete bugs administrators can do everything members can do and can also modify project and environment settings regenerate the api key promote and demote members to administrator status and modify delete others comments owners each project has only one can do everything administrators can do and can also delete the project and reassign ownership recording and categorizing occurrences client specific information the client library identifiers used throughout the website determine how a bug reported from that library is presented in the view the occurrencescontroller index fields constant maps a client library identifier to the relevant summary fields to display in the list view each occurrence is transmitted with the name of the client library the occurrence records this to the client field the bug s client field is set from the first occurrence s in general one should expect that all occurrences of a bug share the same client value regardless of the occurrence s client value all fields for which there is data are displayed in the occurrence view if a client library is updated to add new information fields all that is needed is to update the has metadata hash in occurrence with the new fields and to update the occurrences show view as necessary the index fields hash can also be updated as appropriate if a new client library is added in addition to doing the above for any new fields unique to the new client the index fields hash will need to be expanded to include the new client queue consumer for information about the background worker that converts incoming exception information into occurrence and bug records including doing best guess commit blaming determining which occurrences share the same root bug etc see the documentation for the occurrencesworker module see also static analysis below deploys and releases squash can handle both deployed projects hosted projects for which typically only one version is live at a time and released projects distributed apps for which many versions may exist in the wild if you are developing a released project you must associate your deploy objects with a unique version identifier such as a build number you must also send the correct build identifier with every occurrence report see the client library and api controller documentation for more information once this is done squash s behavior is changed slightly bugs that are fixed in an older release but recur are not reopened bugs that are fixed in an older release but then recur in newer releases are treated as completely separate bugs this app exposes an api endpoint for notifying squash of new releases deploys of your project you should notify squash whenever you deploy your project or release a new version so that it can properly manage bugs automatically mark fixed bugs as deployed associate new bugs with the new deploy etc most client libraries include an easy means to add this feature to your deploy or release process static analysis message normalization when an occurrence is grouped into a bug its message is stripped of any non relevant or situational information note that since the message is not used as a dimension in grouping occurrences two occurrences of the same bug could have completely different messages a bug gets its message from its first occurrence this is done by subclasses of blamer base for most messages this is done using simple regex subsitution squash can also normalize an exception s message using a list of known message templates such templates are stored in the data message templates yml file the file contains a hash mapping exception class names to an array of arrays each inner array contains two elements the regexp to match the exception message on and the replacement message should it match these templates are evaluated in the order they appear in the array scripts that regenerate the templates for mysql and postgresql error strings can be found under the script directory version control systems as of now squash is only compatible with projects that are version controlled using git however in the interest of remaining as vcs agnostic as possible commit identifiers are never called sha1s but instead ids unsymbolicated obfuscated or minified stack traces client libraries of compiled obfuscated or minified applications will need to convert their stack traces in order for them to be of use for static analysis because release builds are typically not distributed with embedded decompilation information a mapping or table must be given to squash so that when squash receives an unconverted stack trace it can perform lookups and convert it to a more usable format currently the supported conversions are symbolication of ios exceptions see symbolication deobfuscation of java exceptions see obfuscationmap and source mapping of javascript exceptions see sourcemap client libraries are responsible for delivering the raw stack trace data to squash when an exception occurs and for delivering lookup tables to squash upon each new release api v1controller has endpoints for these purposes in various languages unconverted stack traces are stored in a particular format see occurrence for more information when a new exception with a stack trace in this format is received squash immediately attempts to convert it using an existing matching lookup table if no such table is found the stack trace is left unconverted it can still be viewed on the front end when later a new lookup table is added squash automatically finds and converts any matching stack traces because every new occurrence must be assigned a bug including unconverted occurrences it is possible that the blamed file and line fields of the bug could themselves be unconverted the bug class has provisions to support this see in particular bugs special file specs all models controllers and library files are unit tested with rspec specs under the spec directory run unit tests with the rspec spec command views and javascript files are not specced no integration or acceptance tests are written almost all unit tests use factories rather than mocks putting them somewhat closer to integration tests in general the test environment is identical to the development production environment save for the usual rails allowances and the config initializers active record observer hooks rb file this file adds after commit hooks to observers identical to those available to models however specs are transactionalized meaning that these hooks wouldn t run until after the spec is completed resulting in multiple spec failures to remedy this the file introspects on the environment and instead links the observer hooks to the after save model hooks in the test environment this differentiates the test and live environments but allows specs to pass if you wish to bring your test environment closer to production you can set the use transactional fixtures rspec setting to false the hooks file will automatically detect the change and use the correct after commit hooks currently all specs pass with and without transactionalized fixtures third party integrations squash supports integration with a handful of popular other developer tools pagerduty when squash is integrated with pagerduty it will begin sending exceptions to pagerduty once the occurrence count for a given bug exceeds the project s critical threshold thereafter every occurrence is sent to pagerduty as a trigger the triggers are grouped into alerts by bug so users will only be paged once per new error in addition marking a bug fixed will also automatically resolve its associated pagerduty alert if any and assigning a bug or marking it irrelevant automatically acknowledges any associated pagerduty alert in order to integrate squash with pagerduty you must 1 generate an api key that squash can use for pagerduty access you must be a pagerduty admin to do this 2 update the config environments common pagerduty yml file to enable pagerduty integration and provide the api key 3 configure generic api services for each escalation policy you wish to use and 4 set the pagerduty related options in your project s configuration page jira when squash is integrated with jira users have the option of associating a jira issue with any bug the management tab will then display a link allowing the user to quickly view the associated issue in addition the user can have squash watch the jira issue for status updates once the jira issue is resolved or is changed to someother specified status the bug can be automatically marked as fixed by associating multiple bugs with one jira issue in such a manner a user can quickly fix a large number of bugs by closing just one jira issue finally a create jira issue button is provided on the management tab allowing users to easily create new jira issues for any bug in order to integrate squash with jira you must 1 configure the config environments common jira yml file with your jira authentication credentials and installation location and 2 add a cron job or other periodic task that runs rake jira update jira integration works out of the box if you use username password authentication oauth authentication requires a few more steps because oauth authentication requires user actions you will need to obtain an access token and secret which the jira client can use without needing to prompt the user you can do this by running the jira oauth rb script ruby rails runner script jira oauth rb follow the instructions to set up your jira integration | front_end |
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FreeRTOS_STemwin_FatFS_CAN_USB | freertos stemwin fatfs can usb | os |
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designdeck | res designdeck png overview design deck is an open source collection of 230 system design flash cards it helps you prepare and succeed in your system design interview the topics covered are the following cache cache md eviction locations strategies when to use a cache etc cloud cloud md main cloud components database db md acid cap partitioning consistency isolation denormalization etc design design md general topics such as idempotence bloom filter causality asynchronous communications vector clocks http http md main http knowledge kafka kafka md main kafka building blocks math math md discrete math network network md tcp cors ping heartbeat osi etc reliability reliability md reliability patterns security security md main security knowledge such as tls cipher encryption anki deck anki https apps ankiweb net is a free software windows mac linux iphone android which makes remembering things easy it utilizes spaced repetition which is a proven technique to increase the rate of memorization http img youtube com vi ummrjrzpme 0 jpg http www youtube com watch v ummrjrzpme spaced repetition the most powerful study technique spaced repetition the most powerful study technique on youtube the single biggest change that anki brings about is that it means memory is no longer a haphazard event to be left to chance rather it guarantees i will remember something with minimal effort that is anki makes memory a choice michael a nielsen augmenting long term memory using anki is a great way to prepare your system design interview here is a flashcard example res anki png the anki version a clone of the 200 flashcards from this repo is available via a one time github sponsorship tier for 21 sponsor https github com sponsors teivah one time tab access to the latest anki deck version of design deck tier cards index cache cache aside cache md cache aside cache aside vs read through cache md cache aside vs read through cache eviction policy cache md cache eviction policy cache locations cache md cache locations cache refresh ahead cache md cache refresh ahead cache write through vs write back cache md cache write through vs write back four main distributed cache benefits cache md four main distributed cache benefits main metric for cache cache md main metric for cache read through cache cache md read through cache when to use a cache cache md when to use a cache cloud cdn cloud md cdn db 3 main reasons to partition data db md 3 main reasons to partition data acid property db md acid property anti entropy db md anti entropy byzantine fault tolerant db md byzantine fault tolerant calm theorem db md calm theorem cap theorem db md cap theorem caveat of serializability db md caveat of serializability chain replication db md chain replication chain replication vs consensus db md chain replication vs consensus change data capture cdc db md change data capture cdc concurrency control db md concurrency control consensus db md consensus consistency models db md consistency models cqrs db md cqrs crdt db md crdt crdt and collaborative applications e g google docs db md crdt and collaborative applications eg google docs db indexes tradeoff db md db indexes tradeoff db internal components db md db internal components db read vs write heavy latency vs consistency availability vs consistency acid vs non acid db md db read vs write heavy latency vs consistency availability vs consistency acid vs non acid delta crdts db md delta crdts denormalization db md denormalization design consideration when partitioning data db md design consideration when partitioning data downside of distributed transactions db md downside of distributed transactions event sourcing db md event sourcing eventual consistency requirements db md eventual consistency requirements examples of solutions offering leader election abstractions db md examples of solutions offering leader election abstractions federation db md federation fencing token db md fencing token gossip protocol db md gossip protocol graph db main use case db md graph db main use case hinted handoff db md hinted handoff hot spot in partitioning db md hot spot in partitioning in a database strategy to handle rebalancing db md in a database strategy to handle rebalancing isolation levels db md isolation levels known crdts db md known crdts last write wins lww db md last write wins lww leader election db md leader election lsm tree db md lsm tree lsm tree vs b tree db md lsm tree vs b tree main difference between consistency models and isolation levels db md main difference between consistency models and isolation levels merkle tree db md merkle tree monotonic reads consistency implementation db md monotonic reads consistency implementation mvcc db md mvcc n 1 select problem db md n1 select problem nosql main types and main architecture principles db md nosql main types and main architecture principles operation based crdts db md operation based crdts operational transformation ot concept and main drawback db md operational transformation ot concept and main drawback optimistic concurrency control pros and cons db md optimistic concurrency control pros and cons pacelc theorem db md pacelc theorem partitioning sharding db md partitioning sharding partitioning criteria db md partitioning criteria partitioning methods db md partitioning methods quorum db md quorum raft db md raft read repair db md read repair relation between replication factor write consistency and read consistency db md relation between replication factor write consistency and read consistency replication vs partition impacts db md replication vs partition impacts schema on read vs schema on write db md schema on read vs schema on write serializability db md serializability serializable snapshot isolation ssi db md serializable snapshot isolation ssi single leader multi leader leaderless replication db md single leader multi leader leaderless replication sloppy quorum db md sloppy quorum snapshot isolation si db md snapshot isolation si snapshot isolation common implementation db md snapshot isolation common implementation sstable db md sstable state based crdts definition and requirements db md state based crdts definition and requirements strong eventual consistency definition and requirements db md strong eventual consistency definition and requirements three phase commit 3pc db md three phase commit 3pc transaction db md transaction two main approaches to partition a table that has secondary indexes db md two main approaches to partition a table that has secondary indexes two types of crdts db md two types of crdts two phase commit 2pc db md two phase commit 2pc wal db md wal when relational vs when document db md when relational vs when document when to use a column oriented store db md when to use a column oriented store why db schemaless is misleading db md why db schemaless is misleading why is in memory faster db md why is in memory faster write and read amplification db md write and read amplification write heavy and replication type db md write heavy and replication type design auditing design md auditing backward vs forward compatibility design md backward vs forward compatibility bloom filter design md bloom filter causality design md causality concurrent operations design md concurrent operations consistent hashing design md consistent hashing design impacts of sharing design md design impacts of sharing design read heavy vs write heavy impacts design md design read heavy vs write heavy impacts different types of message failure design md different types of message failure event log vs message queue design md event log vs message queue exactly once delivery design md exactly once delivery flp impossibility design md flp impossibility geohashing design md geohashing hashing definition and size of md5 and sha256 design md hashing definition and size of md5 and sha256 hdfs design md hdfs how to reduce sharing design md how to reduce sharing hyperloglog design md hyperloglog idempotent design md idempotent latency numbers every programmer should know design md latency numbers every programmer should know lease design md lease least loaded endpoint load balancing strategy design md least loaded endpoint load balancing strategy liveness property design md liveness property load balancing design md load balancing load shedding design md load shedding locality design md locality log design md log log compaction design md log compaction main drawback of shared nothing architectures design md main drawback of shared nothing architectures mapreduce design md mapreduce microservices pros and cons design md microservices pros and cons number of values to generate to reach 50 chances of collision 32 bit 64 bit and 128 bit hash design md number of values to generate to reach 50 chances of collision 32 bit 64 bit and 128 bit hash orchestration vs choreography design md orchestration vs choreography outbox pattern design md outbox pattern perfect hashing design md perfect hashing quadtree design md quadtree rate limiting throttling definition and algos design md rate limiting throttling definition and algos rebalancing design md rebalancing rest design md rest rest vs grpc design md rest vs grpc safety property design md safety property saga design md saga scalability design md scalability scalability ceiling design md scalability ceiling shared nothing architectures design md shared nothing architectures source of truth design md source of truth split brain design md split brain throughput design md throughput total vs partial order design md total vs partial order uuid design md uuid validation vs verification design md validation vs verification vector clock design md vector clock why asynchronous communication design md why asynchronous communication http 301 vs 302 http md 301 vs 302 403 or 404 http md 403 or 404 cookie http md cookie four main http 2 features http md four main http2 features hls http md hls http http md http http cache control header http md http cache control header http etag http md http etag http keep alive http md http keep alive http methods safeness and idempotence http md http methods safeness and idempotence http safe method http md http safe method http status code 429 http md http status code 429 http status codes http md http status codes what happens if you type google com in your browser http md what happens if you type googlecom in your browser kafka consumer types kafka md consumer types durability availability and latency throughput tradeoffs kafka md durabilityavailability and latencythroughput tradeoffs log compaction kafka md log compaction offset kafka md offset partition kafka md partition partition distribution kafka md partition distribution rebalancing kafka md rebalancing segment kafka md segment shared subscription kafka md shared subscription math associative property math md associative property commutative property math md commutative property harmonic mean math md harmonic mean network arp protocol network md arp protocol average connection speed in usa network md average connection speed in usa backpressure network md backpressure bandwidth network md bandwidth bgp network md bgp cors network md cors difference ping heartbeat network md difference ping heartbeat difference tcp udp network md difference tcp udp difference view materialized view network md difference view materialized view dns network md dns dns lookup push or pull network md dns lookup push or pull health checks passive vs active network md health checks passive vs active internet model network md internet model layer 4 vs layer 7 load balancer network md layer 4 vs layer 7 load balancer mac address network md mac address max size of a tcp packet network md max size of a tcp packet mqtt lwt network md mqtt lwt ntp network md ntp osi model network md osi model routers network md routers routers buffering network md routers buffering routers processing network md routers processing routing table network md routing table service mesh network md service mesh switch network md switch tcp congestion control network md tcp congestion control tcp connection backlog network md tcp connection backlog tcp flow control network md tcp flow control tcp handshake network md tcp handshake websocket network md websocket why can t we rely on the system clock in distributed systems network md why cant we rely on the system clock in distributed systems reliability bulkhead pattern reliability md bulkhead pattern cascading failure reliability md cascading failure causal consistency implementation reliability md causal consistency implementation circuit breaker reliability md circuit breaker exponential backoff reliability md exponential backoff fault tolerance reliability md fault tolerance jitter reliability md jitter knee point reliability md knee point phi accrual failure detector reliability md phi accrual failure detector retry amplification reliability md retry amplification security authentication security md authentication certificate authorities security md certificate authorities cipher security md cipher confidentiality security md confidentiality integrity security md integrity mutual tls security md mutual tls oauth 2 security md oauth 2 public key infrastructure pki security md public key infrastructure pki tls handshake security md tls handshake two main uses of encryption security md two main uses of encryption two types of encryption security md two types of encryption what does digital signature provide security md what does digital signature provide what does tls provide security md what does tls provide references designing data intensive applications https dataintensive net understanding distributed systems https understandingdistributed systems distributed systems for practitioners https leanpub com distributed systems for practitioners additional notes if you re preparing an algorithm data structure interview you can take a look at algo deck https github com teivah algodeck | interview interview-preparation leetcode system-design cache cloud database http kafka network reliability scalability security | os |
theres-a-note-for-that | theres a note for that decription this project allows the user to keep all their notes in 1 location where they can come back anytime the objective of this project is to give experience to us to show how to connect a front end applications to the back end this application allows the user to create view and delete their notes below is the cirteria for passing user story as a small business owner i want to be able to write and save notes so that i can organize my thoughts and keep track of tasks i need to complete acceptance criteria given a note taking application when i open the note taker then i am presented with a landing page with a link to a notes page when i click on the link to the notes page done then i am presented with a page with existing notes listed in the left hand column plus empty fields to enter a new note title and the note s text in the right hand column done when i enter a new note title and the note s text then a save icon appears in the navigation at the top of the page done when i click on the save icon then the new note i have entered is saved and appears in the left hand column with the other existing notes done when i click on an existing note in the list in the left hand column then that note appears in the right hand column todo when i click on the write icon in the navigation at the top of the page then i am presented with empty fields to enter a new note title and the note s text in the right hand column link live link to appication https theres a note for that herokuapp com screenshots homepage deploy 20images screen 20shot 202022 11 02 20at 202 44 01 20pm png note page deploy 20images screen 20shot 202022 11 02 20at 202 46 24 20pm png | server |
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real_estate_ml | real estate ml machine learning for real estate you may want to run jupyter in this mode jupyter notebook notebookapp iopub data rate limit 10000000000 zillow api sign up to sign up for the zillow api https www zillow com howto api apioverview htm download zillow zillow data can be downloaded from site here https www zillow com research data exploratory data analysis jupyter notebook with plotly integration doing zillow data exploration https github com noahgift real estate ml blob master notebooks explore zillow data sets ipynb plotly graphs plotly interactive chart 30 year history of real estate usa https plot ly ngift 9 30 year history of real estate usa https user images githubusercontent com 58792 33234951 e89a4d86 d1e3 11e7 94bc 6ca8ce336104 png plotly interactive chart bay area median prices single family homes https plot ly ngift 7 bay area median prices single family homes https user images githubusercontent com 58792 33234931 90cfd350 d1e3 11e7 94d4 61e6e7ed11d0 png | python pandas scikit-learn knn plotly jupyter-notebook machine-learning real-estate unsupervised-learning | ai |
HKU-DASC7606-A1 | assignment 1 computer vision object detection for autonomous driving in this assignment you will develop an object detection system for autonomous driving you are required to implement a simple detection network called hkummdetector na ve version with resnet as backbone and yolo as detection head through this assignment you are expected to learn about designing and optimizing an object detection network github link https github com liang zx hku dasc7606 a1 https github com liang zx hku dasc7606 a1 pdf file problem description pdf problem description pdf new q a document q a with some introductory material https connecthkuhk my sharepoint com w g personal liangzx connect hku hk eswf67sry4figwsd 1rl4iobank7qpcyd5jehtd605 apw e jhy6jt authors tas zhixuan liang haibao yu date 2022 12 this codebase is only for hku dasc 7606 2022 2023 course please don t upload your answers or this codebase to any public platforms e g github before permitted all rights reserved 1 problem description and assignment objectives 1 1 what is object detection for autonomous driving object detection is one of the most essential tasks in autonomous driving this task aims to recognize and localize traffic participants like cars in the road scene from images or point clouds this assignment focuses on solving the detection problem from a single image image resources image png div align center img src resources demo jpg height 300 div p align center figure 1 a visualization example of object detection for autonomous driving p 1 2 what will you learn from this assignment understand the basic theories of deep learning exspecially for object detection task such as the networks of resnet https arxiv org abs 1512 03385 and yolo v1 https arxiv org abs 1506 02640 the detection loss function and important concepts of object detection e g roc curve and mean ap apply object detection algorithm to solving autonomous driving problem such as detecting cars and pedestrians in the traffic environment gain experience of implementing neural networks with a popular deep learning framework pytorch https pytorch org develop a deep learning system from scratch including network design model training hyperparameter tuning training visualization model inference and performance evaluation spontaneously and deeply explore advanced solutions for object detection task italics indicate bonus requirements the same below 1 3 what should you prepare for this assignment master the basic use of python and pytorch be familiar with the resnet https arxiv org abs 1512 03385 be familiar with the yolo v1 https arxiv org abs 1506 02640 you can learn about them step by step in the process of completing this assignment 2 assignment tasks you must fill in the blanks and submit the completed codes for this assignment with the provided codebase this assignment offers an incomplete codebase for object detection with modified yolo v1 https arxiv org abs 1506 02640 you must submit the test data s model outputs with your completed codes now the test data has been released here https drive google com file d 1 i1rp1vrf4s5hx9 x3mul50c10ph1tqe view you should utilize hyperparameter tuning and other widely used techniques to improve detection performance you must submit a maximum of 6 page technique report to explain how you improve the object detection performance besides some visualization results e g loss curve are encouraged in this report shell download this project git clone https github com liang zx hku dasc7606 a1 git cd hku dasc7606 a1 2 0 dataset preparation the dataset is available here https drive google com file d 1whc8asloaeuipgcqqncyir9q kb9metc view usp sharing the dataset is composed of train val test parts and their corresponding annotations please refer to src data readme md src data readme md for the dataset strcuture explanation for your convenience you can download the dataset through the following command shell cd src chmod x data download2 sh data download2 sh 2 1 submit the completed codebase the codebase src src is organized as followings src data dataset py dataloader download sh script to download dataset model block py backbone head py detection head hkudetector py object detection network utils loss py util py train py model training predict py model inference eval py performance evaluation task 1 filling in the backbone with resnet you should fill in two blanks in file src model block py src model block py to complete the basic blocks of backbone network including the block design and forward function you should try to apply the resnet into the backbone the resnet architecture is as the following image resources image png div align center img src resources resnet arch png height 200 div p align center figure 2 a visualization illustration of basic block and bottleneck block in resnet p task 2 filling in the detection head you should fill in one blank in file src model head py src model head py task 3 filling in the network you should fill in three blanks in file src model hkudetector py src model hkudetector py task 4 filling in the object detection loss function you should fill in three blanks to complete object detection loss in file src utils loss py src utils loss py the object detection loss includes five terms as following which is equation 3 in yolo v1 https arxiv org abs 1506 02640 you are required to complete two terms of them begin aligned loss lambda text coord sum i 0 s 2 sum j 0 b mathbb 1 i j text obj left left x i hat x i right 2 left y i hat y i right 2 right lambda text coord sum i 0 s 2 sum j 0 b mathbb 1 i j text obj left left sqrt w i sqrt hat w i right 2 left sqrt h i sqrt hat h i right 2 right sum i 0 s 2 sum j 0 b mathbb 1 i j mathrm obj left c i hat c i right 2 lambda text noobj sum i 0 s 2 sum j 0 b mathbb 1 i j text noobj left c i hat c i right 2 sum i 0 s 2 mathbb 1 i text obj sum c in text classes left p i c hat p i c right 2 end aligned to help you better understand and implement the loss function we can split this equation into four parts you will find it helpful when you do the task 4 the first two terms forms the location loss the third term is the iou loss for boxes containing the objects the fourth term represents the loss for boxes not containing the objects not iou or no objects and the last term is the classification loss hint in implementation the fourth term is split into two part part i not response loss for the box containing the object but not the one with the maximum iou part ii no onject loss for the box not containing objects task 5 filling in the training pipeline we have implemented dataset preprocessing codes for you we strongly suggest you to read the src data dataset py src data dataset py carefully before completing the following tasks you should fill in two blanks to complete the training pipline in file src train py src train py after completing the training pipeline you can run with the following command bash python train py output dir checkpoints task 6 filling in the prediction pipeline and non maximum suppression you should fill in two blanks to complete the prediction pipeline and the nms in the file src utils util py src utils util py non maximum suppression is a computer vision method to select a single entity from many overlapping entities for more details refer to nms algorithm https learnopencv com non maximum suppression theory and implementation in pytorch after completing the inference pipeline you can run in the following command the visualization result will be saved in vis results folder and you should show some of your results in the final report bash python predict py image path ass1 dataset test image 000001 jpg vis dir vis results task 7 filling in the evaluation pipeline to understand map you should fill in one blank to complete the map calculation in file src eval py src eval py the map is one of the most essential evaluation metrics in object detection for more details refer to map calculation https jonathan hui medium com map mean average precision for object detection 45c121a31173 after completing the evaluation pipeline you can run in the following command important you should submit the result pkl generated in this part submission details are illustrated in sec 3 1 bash python eval py split test output file result pkl hint please pay attention to the threshold set in the evaluation pipeline we suggest setting pos threshold 0 1 and we will perform lower truncation on pos threshold that is all pos threshold 0 1 will be truncated to 0 1 2 2 submitting the model outputs of the test data you should train your model on the train val part and you should generate and submit the outputs of the test part with your trained detection model the test part is released here https drive google com file d 1 i1rp1vrf4s5hx9 x3mul50c10ph1tqe view and you can download using the src data download test sh src data download test sh bash cd src chmod x data download test sh data download test sh you can generate the final result using the following command please specify the image size here if you change it to a larger scale bash python for submit py split test output file result pkl model path your best ckpt file image size your image size task 8 improving the detection performance in this task you should try different techniques to improve the detection performance such as using grid search for the proper hyperparameters modifying data preprocessing methods changing the batch size replacing the optimizer and so on you should generate the prediction outputs with the trained detection model on the test data the output organization should follow the form in the next section bonus task 10 more beyond full mark improving the detection performance with more advanced architecture you are encouraged to explore and implement more advanced network architectures on this task if you have any tries on this part you should submit all your codes model output and the report to explain your understanding about how to improve the detection performance with more advanced architecture you should explain why these improvements can enhance the performance in your own words instead of just cloning some codes and performing inference bonus score will be given based on your overall contributions on these three parts 2 3 submitting the reports task 9 explaining the efforts to improve the detection performance in experiment report you should submit a experiment report to describe how you take efforts to improve the object detection performance you should also provide the loss curve of your training procedure and figure out when the model converges in the curve you can further explain whether training epoch and batch size affect the result in this report 3 submission forms and score scheme 3 1 submission file forms the submission files should follow the specific organized forms as following since tas have to rerun your code on another test dataset marks will be deducted multiplied by 80 if your code cannot be run because your submission of code does not follow our specified instructions tas may contact you to solve related problems uid name assignment 1 your submission file name src the completed source codes corresponding to sec 2 1 you should keep the same organization with the original file structure bonus1 src the source codes for more advanced architecture if there are any outputs your model outputs on test data result pkl it will be generated automatically in src eval py please follow the format in source code bonus1 pkl the results of your more advanced implementation if there are any bonus2 pkl report pdf combine the experiment analysis report and the survey analysis report in one pdf file 3 2 score scheme the final score of the assignment is composed of four parts 1 the codebase you complete 30 2 the detection performance 50 3 the experiment analysis report 20 1 for the completed codebase 30 the mark will be given mainly based on completeness under the requirements 2 for the performance part 50 ta will rerun your code on another test dataset same distribution as training set and verification set and give your marks based on the map of your model map larger than 42 will get the full mark of this part map between 38 and 42 will get 90 mark of this part map between 34 and 38 will get 80 mark of this part map between 30 and 34 will get 70 mark of this part map between 26 and 30 will get 60 mark of this part map larger than 0 2 will get 50 mark of this part others will get 0 mark 3 for the experiment analysis report 20 the marks will be given mainly based on the richness of the experiments analysis rich experiments detailed analysis 90 100 mark of this part reasonable number of experiments analysis 70 80 mark of this part basic analysis 50 60 mark of this part not sufficient analysis lower than 50 4 text final mark min lbrace 100 text sum of the three parts text bonus mark rbrace 4 working on the environment 4 1 working on the hku gpu you had better know the following things ssh remotely anaconda install pytorch and torchvision with corresponding cuda install packages with pypi use git for version control 4 2 environment setup standard codes have been tested with the following settings it s just a reference for you and there is no need for you to run in the completely same environment python 3 8 pytorch 1 9 1 cuda 11 1 torchvision 0 10 1 cuda 11 1 numpy scipy tqdm opencv python 5 important date assignment 1 release jan 30 mon test data release feb 24 fri released here https drive google com file d 1 i1rp1vrf4s5hx9 x3mul50c10ph1tqe view submission deadline mar 10 fri late submission policy 10 for late assignments submitted within 1 day late 20 for late assignments submitted within 2 days late 50 for late assignments submitted within 7 days mar 17 late 100 for late assignments submitted after 7 days mar 17 late 6 contact any question please contact liangzx connect hku hk or yuhaibao connect hk hk | ai |
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dotfiles | gitter https badges gitter im elasticdotventures community svg https gitter im elasticdotventures community utm source badge utm medium badge utm campaign pr badge project status wip initial development is in progress but there has not yet been a stable usable release suitable for the public https www repostatus org badges latest wip svg https www repostatus org wip b00t b00t cognitive middleware elasticdotventures matrix org presently alpha very unfinished b00t is a polylingual polyframework voice vision cli cognitive format transformer instruction learning approach to automata an idiomatically control language for an assistant that can learn new skills through direction or experimentation using external api provider such as jovo allows b00t to interface with either the pstn phone network or relay through smart assistants targeting cortana google home b00t is built using an open source tool chain inside win11 wsl2 or other linux environment examples of skill target s are ambitious design simulate control and monitor robotic manufacturing cloud infrastructure gpt summarize text and or math write code methods to build develop new skills as directed attend meetings via video audio intercept character avatar synthesis lip sync interactively screen pstn messanger calls sessions make appointments website chat bot write reports visualizations online three js svg collada png maybe excel google sheets write maintain code orm graph schema and interfaces to svg openscad stl collada sql transpilation of python rust typescript wasm skills skills are either bash steps or makefiles which can be automated using ci cd find import 3d objects electronics data sheets to for references in digital shadows future theorize about new object structures physics electro chemistry protein folding etc injest metrics from ebpf hooks for os level threat monitoring telemetry play wingman video games good enough to be fun including social aspects design and print 3d objects assemblies and simulations etc prepare apply video audio for presentations etc purchasing order reconciliation accounting customer service hr using zero code i e node red appsmith or az durable functions these capabilities are rolled up into interactive macros called tasks which when grouped together are called a toil the skills are build in an oregon trail where the operator must decide which tasks are worthy of receiving operating cycles and what if any resources must be used for discovery digestion of new skills in some cases the operator may such as using a mouse joystick voice etc fit the ai by helping it assemble compile etc to teach skills explain materials objects etc the main cost with a system like this is the operational cost might doesn t work the same as an employee being able to consume video audio websites documents data feeds injest participate in social systems such as twitter discord matrix slack ms teams in a poly medium chat interface azure is preferred because sso active directory simplifies a variety of security access control toil in terms of interfacing although at some point i prefer to replace this with zanzibar and offer at least an aws k8s terra form approach but that isn t explicitly necessary for this project since it s all mostly serverless functionally driven smart pipes and should be generic enough that a new software service simply by reading it s api i e an api transpiler that is compatible with one or more of it s messaging or database protocols especially if that s openapi swagger sql graphql or json protobufs it is designed to assist a human or small team but to amplify and obviate the require for most big companies by efficiently replacing people with intelligent robotic process control very wip presently this is only a compendium of my tools undocumented scripts for a future interactive initalization using fzf setup installer i m presently learning rewriting this to rust and solidifying on python typescript interfaces wasm is a dream turns out cargo is amazing and obviates a lot of work rust s complex pattern matching language is awesome reminds me of perl on the embedded side i ve moved from c to rust as well so esp32 s2 c3 are the target hardware platforms but it could run on an rpi or whatever for physical motor sensor i o by generating everything programmatically each physical object will have a digital object shadow that would include inheritance robust math logic to describe how the object is used programmatically describe it s motion etc this makes setting up things like monitoring via opentelemetry straightforward and more standardized across a big complex project for the 3d objects i ve now abandoned my traditional mouse driven parametric cad onshape entirely and moved to freecad so i could use python i ve now discovered openscad and it s vitamin module libraries which aren t terribly well organized i m presently formulating learning how to write a rust transpiler which basically means reading a lot of other peoples rust code into openscad but learning openscad has been awesome rewarding once that task is finished then i will be either begin adding the ai features including clip or cyclegan commands to let the ai design fill textures backgrounds gpt 3 or gpt neox to create svg openscad codex templates i also intend for this eventually to be a massive toil reduction time saver by using git to track approve asset changes objects complex assemblies in sync auto magically automagic without doing file import export between apps presenting the same state across freecad easy blender via collada possibly unity also collada using a git action build chain which can also run locally the resulting approach then be used for visualization simulation training regression testing prior to output of complex fdm 3d printed cnc milled assemblies eventually building toward zero human robotic manufacturing assembly post work once all that is working i will start on the vhdl verilog spicedb pcb circuit simulator as well at which point kicad is the most likely candidate for interface but realistically we ll just be using kicad for it s component libraries and treating the pcb s as complex assemblies this repo is the base it s intended to be used as a project template via a sub module to print in a lot of dependencies and try to provide some harmony to the chorus of oss dev happening around the planet in 2022 the plan is to have a yahoo esque awesome curated list of installable time saving labor reducing tools fundamentals to interface any cloud ai skill next version will feature better docker compose rust cli sharing with contributors advisors feedback testers soon comments issues pr s welcome please keep up to date and get pachyderm support via twitter https img shields io twitter follow b00t style social https twitter com brianhorakh follow us on twitter text plain l b u g s q u 1 s h 1 n g s 0 f t w a r 3 for the benefit of humanity the ultimate compendium of useful multi disciplinary end to end systems engineering toolkit for reduction in difficulty this repo components bash python ts scaffold s shells https starship rs installing termux https doc redox os org ion manual repl html https murex rocks docs guide quick start html https nixos org manual nix unstable command ref nix shell html extensive use of more utils yq jq fzf fdfind etc server architectures x86 nvidia cuda optimized x86 amd64 arm64 rpi alpine planned blocked by 3rd party webinstall dev embedded architectures atmega64 esp32 dev vs code on linux or wsl2 git github issues build ci cd idempotent app templates app config app data app lib app src separated platform io for embedded extensive json yaml toml setup working configurations front end app typescript vue vitesse spa i18n template openauth openid to azure b2c msal2 federated security interfaces rest graphql rxjs zip open opentelemetry setup back end app typescript v4 python 3 9 and others poly lingual container orchestration docker k8 drone ci and others any oci is fine author bias minimalist k8 minikube pachctl data lineage cloud azure google aws ali author bias azure gcp ali aws azure will have the most extensive support initially database ephermal sqlite local sqlite firebird mariadb postgres author bias value engineering to freeze unfreeze projects poly cloud managed firebase nosql etc plurality of storage volume options cloud for online on demand cloud hosted or offline cold messaging protobufs redis rabbitmq zmq mqtt and others security low to perfect per complexity risk requirements poly scenarios artificial intelligence ag robotics hardware sensors iot dev 3d rendering red team cybersecurity ecommerce sales finance accounting chat ops business operations automation crypto banking academic science r d r engineering tiger team problem solving aka math future stack piercer cargo install zellij ebpf filters io uring bindings opentelemetry logging bash bats tap testing https testanything org storytime ai ops interactive voice cli assistant control surface b00t is a cyb3rpunk startup k1t unsuitable for military or antisocial projects per the license for valid inclusion in hackathons elastic license v2 elk2 open license seeking testers investors contributors any feedback peer review star the repo if you think i should keep working on this i m planning to submit this to oreilly as a nutshell book idea b00t from the ground up quickstart bash git clone https github com elasticdotventures b00t git fzf setup tutorial menu bash b00t b00t sh or just load the tooling environment bash source b00t b00t bashrc or checkout the repo 85 of the finished work is presently in the bash folder b00t a view from the ground up b00t is systems engineering poly glue publishing transpiler it will use menus to drive a cli for choosing and updating poly stack scenarios which are infrastructure code templates working samples for all relevant stack layers b00t intends to provide a curated starting point for a variety of poly disciplinary aka complex projects a modern curated catalog of computer interfaces academic and elastic libraries this project was born partially out of necessity and the rest out of pure curiousity for what could be built and how quickly a menu driven oregon trail of architectural templates for a project b00t is colorful and not traditional it is cheeky but non discriminatory it is poly lingual but it may not be suitable for traditional corporate or government environments as such it is better suited for the home inventor hobbyiest or open source hardware developer fabricator children under 16 should ask your parents before using b00t emoji and ideogram based utf8 i18n called storytime v1 naming conventions for an oregon trail themed menu or anything goes cli project init to exit coverage this non traditional approach offer faster diagnostics and efficient operational characteristics allowing svelte teams for ops scaffolding for containers installation of development environment naming with emoji is improved with menus intellisense editors and cli tab completion b00t heavily uses vs code extensions for read write running private or hosted zero code engines an artificially written operated infrastructures ai ops hopefully improving indivual productivity to 100x for creating poly disciplinary projects presently b00t hopes to become a modern slackware built on linux a deployable yahoo directory of open source with some light tutorial learn only what you desire to with some minimal explanation of truth consequences oregon trail of decisions framework for generating idempotent templates to build complex maintainable efficient systems engineering principles b00t will attempt to present itself in many formats and give operators a massive common arsenal of pre interoperably configured tools example projects in python typescript bash etc poly lingual as well as popular patterns for integrating tools from the ground up b00t includes some strong opinions such as vs code development environment b00t can be thought of as a cloud shell enhancement and it s primary role is as a catalyst to easily deploy a reliable pattern for interconnection between applications a menu driven or cli driven poly stack poly interface poly software awesome distribution examples of complex json yaml manipulation complete automation of daily activities ultimately i hope to add a cli voice interface based on jovo something like how tony stark interacts with jarvis for software projects and it could sell support and provision the software to accomplish this i need to structure this repo tools in a uniquely b00t way which i m attempting to make easier for myself and hopefully you b00t is variable low to high security postures for example there are a variety of security postures available from secret keys stored in a local env file a self hosted vault or a cloud based key repository protocols packages have been curated based on their utility in poly lingua poly cloud technology library aka b00t the key is providing a known set of steps to differentiate the posture between dev build release b00t framework itself is k8 minimalist but very pro git pipelines automation k8 kubernetes should only be used when it is absolutely necessary and then as sparingly as possible pipelines idempotentent containers those are 100 awesome k8 support is my present area of improvement in bash scripting todo trying not to re invent the wheel found a bunch of new tools and refactoring mid project bsfl https github blog 2015 06 30 scripts to rule them all https github com bashup devkit https github com bashup mdsh https github com bashup events https github com bashup lore https github com bashup loco azure graph openid authentication scaffold in typescript spa vue vite vitesse based template please excuse the scattered bits work in progress you might try the setup file or explore the color repo bash cd b00t 01 startup sh is presently suitable for probably absolutely nobody besides brian horakh the author but i welcome anybody with similar passions in pre dev stage projects incubators self reliant engineering teams no vendor support except the author git issues who want to sponsor my progress or would like to use this framework in their own companies sponsor through github or the b00t ethereum address is https vittominacori github io ethereum badge detail html address 0x24bd79c0efff201bd5b24b622d5ea09f93dbfaa3 please note goes a long way towards demonstrating to my wife that this warrants the amount of attention i give it versus her projects thanks ask for if you want social likes github twitter follows share with your friends b00t vision a multi stack directory from the ground up with directory of poly lingual interfaces like docker moby b00t is for ai robotics cybersec code hackathon groups or red teams who need to tandem or poly hackathon global startup code a thon who need fast iteration and shared debugging hackers who want to deploy multi language code across serverless functions docker containers in azure system engineers or integrators building a container system application developers looking for an easy way to run their python typescript and related applications in containers with vs code azure tooling best practices b00t intends to provide an early stage complete open ops stack for a company examples included to quickly easily and affordably minimize and compartmentalized best practices templates for pr0j3ct design caching and also runtime isolation for offpeak processing saving m0n3y other layers included to reduce costs and monitor integrity but can also be accessed as a slimmed down bare os and should probably work in anything which can run aptitude package manager usually debian ubuntu this targets ubuntu all architectures what b00t intends to provide functional examples opinionated toolchoices vs code dev environment plugins fzf menuing and high automata with detailed config notes repeatable clean environment with sane defaults that can be easily disabled i e remove python or remote typescript select database deployment zones etc for application developers application design best industry practices security built in oauth openid hardened determinsic patterns using azure durable functions multi facet ideogram cyb3rpunk emoji pinyin filled logs metrics such 3117 multi stage dev build test deploy ci cd is presently done through github azure app services containerized projects using k8 esque pipelines especially well suited for machine learning create cloud deploy pipelines bi lingual projects using python typescript or others your project demo modules roadmap using b00t v0 present work in progress v1 aiia call center http github com elasticdotventures aiia callcenter small business nlp tts stt call center intelligent assistant based on jovo framework with additional interfaces for discord slack bigcommerce integration planned v2 dongxi inventory http github com elasticdotventures dongxi discrete inventory accounting ethereum solidity interfaces bigcommerce integration v3 gr0w p0t b0t http github com elasticdotventures gr0w p0t b0t ai driven hydroponic biogenesis appliance hydroponic farm controller built on esp32 with ai currently under development internal libraries and essential tooling docker deploy then integrate az with bicep fzf menus installer b00t the vision what about b00t elasticdotventures b00t is a highly opinionated set of tools for deploying azure cloud services with ev libraries called c0re mostly for azure b00t brings together a plurality of powerful cloud tools to to encourage a non traditional but extremely p0werful mix martial art of code which itself is a curated catalog of utilities to manage infrastructure as code presently dev ops but with an eye toward future ai ops this text here is mostly visionary explaining the what about b00t which is presently early stage being re b00t ed from my prior projects b00t syntax rationale the b00t approach uses incorporates 1337 speak for c0mm0n words to encourage brevity at all layers the 1337speak used in b00t is primarily used to make unique pnemonics that are substantially easier to grep during a subsystem trace across layers in the stack thus providing f1ng3r printing glue itself isn t a tool it s designed to demonstrate how to deploy for example deploy a harware or machine learning transformer models affordbly at scale the naming models create colorful and meaningful filters to radically improve code quality debuggability and incorporating zero code deterministic actions azure logic functions the higher visual payload of short 1 4 character emoji hsk1 in names is informative and has valuable screen real estate win is emoji keyboard in windows but emoji with cut and paste intellisense make this easier than you d think especially when you type d0cker and a pops up in spell check using a custom dictionary 1337 mechanics generally indicate logical role or purpose using tab complete or mouse hover in vs code intellisense ide and cli makes it easy and artistic on the screen reinforcing art in code b00t focusing on the pictures and basic glyph optimized based simplified mandarin only reading the code when it s necessary since the human brain is better at visual pattern sorting than it is reading this approach allows for grouping by symbol and simplifies some aspects of command line searching properties test generation and several other aspects built to deploy azure logic connectors azure durable functions with python typescript connectors azure service bus azure keyvault configs azure arm bicep check jargon md for more the full glossary naming conventions docker python typescript emoji indicates things like designee consignee etc this is an important aspect of the storytell logging storytell creates really colorful transaction logs error dumps these will eventually be extended to perform basic ml application forensics monitoring these meta patterns using computers to monitor computers helps our soon to be obsolete primate brains abstract patterns that wouldn t be nearly as obvious in regular english text and notice problems and inform the determinisitic control surfaces to take action isolate block hold ignore with possible consequences this isn t the whole application freezing it s a message in an application or a corrupt video frame grabber in a video stream any payload which doesn t match the model it s not lost forever it s simply flagged for review emoji in code one of the most controversial aspects of b00t is it s heavy use of emoji and pinyin the reality is nlp natural language processing of english is really difficult expensive less reliable than the one character per word symbol approach in the b00t world any emoji which is red in color is bad a warning color if a build process has any red symbols that appear that s a problem even the cherry is reserved as a missing element a token which the user could solve and maybe someday earn points b00t is bi lingual one of the c0des it understands is bash script here s a sample bash function taken from the c0re to see if a machine is running windows system for linux version 2 abbreviated to wslv2 the emoji colorfully demonstrates this bi lingual principle bash microsoft windows linux subsystem ii https docs microsoft com en us windows wsl install win10 function is wslv2 v2 return cat proc version grep c microsoft standard wsl2 and here s how to decode it penguin linux tux mascot blue heart microsoft google aws windows self explanatory may not appear on android so without knowing what wslv2 is using only three symbols you can infer a lot about it disclaimer this is alpha software b00t is provided as is b00t is rique nfsw for example a default project could be auto named butt plug or something like that it s intentionally cheeky and non discriminatory b00t contains a powerful build process that can muster substantial resources mixed martial art of coding storytime logging b00t is designed around the idea of storytime logging that includes emoji hsk 1 chinese vocabulary please don t be intimidated default settings leave english translations on the author brianhorakh is a native english speaker and multi language polygot spanish mandarin italian german all have their own linguistic style and strengths think of this as mixed martial art of coding i m not suggesting anybody actually learn chinese your browser already knows it install google translate right click any symbol tf use pinyin how much information can be transmitted in a symbol vs a character hsk1 is level 1 chinese mandarin language using simplified pinyin symbols ideograms for action commands and stack layer naming conventions designators for frontend qi nmi n backend b imi n in correct chinese files would be named like this file relates to the front end file backend but wait why waste a character file front end firewall file backend container now let s add some emoji file front end firewall file backend container these are only illustrative examples to you show you symbology using a browser plugin you can translate anything in the documentation easily but by integrating b00t scripting at various stages it produces a well defined pattern based marshalling summary layer of logic for inputs and outputs of different subsystems simplified pinyin is a screen glyph optimized font that means hsk1 characters are by design very easy to read learn presently emoji pictograms are second class languages are regionally ambiguous i e has a plurality of meanings see jargon md readme syntax md wait what does b00t do b00t is a novel and opinionated pipeline orchestration system with integrated vs code development environemnt ci cd pipeline base system which is suitable for deploying any cloud scale state less machine learning project in frameworks such as nvidia cuda pytorch tensorflow etc as desired b00t provides the base idempotent templates for resources public private code libraries written in azure arm bicep the ultimate output is a fully operational cloud resource group sensibile file shares key vaults monitoring logging scaffold skeletons in ts python as well the c0re which presents itself as an interactive filesytem blob storage python typescript bindings i ll eventually add some higher level vue templates and hardware iot arduino esp32 templates as well one unique aspect of b00t is that it will allow the ultimate images to be removed using docker dive during the publish to live production from the b00t perspective it s going to help you build something it s only a foundation further application templates can be built on b00t and then easily upgraded taking advantage of new features in cloud based determinsic systems such as azure logic functions containers can be frozen fully loaded or kept hot with standbys based on a load balancer such as a cloud function or container can be readonly nvm e backed memory blob that is awaiting a trigger probably by an inbound http websocket e poll or io submit the published container can be stripped down thus improving both size security posture by removing tools configuration files from public facing images cloud based appconfig stores keyvaults are used keyvaults contain types that are first order types which are aware the passwords etc in them must be kept secure for example in azure logic functions secure tokens such as passwords or access keys from a vault are tagged and automatically beautifully filtered from logs as well this makes compliance user privacy easier extensive use of pipelines and messaging queues allow for tests and other large jobs to be run in parallel at cloud scale why is b00t opionated mean for example b00t believes that vs code with it s intellisense typescript python docker azure aws gcp code auditing and plurality of other useful extensions makes vs code the one true editor the author believes b00t pattern works best when using remote containers which is one of the layers it builds configures the b00t organizational pattern is formatted around an intentionally lean svelte enterprise everything is automated and structured for easy updates using gitops and json debugging is on by default but can be reduced later to save serverless consumption plans are also default and cost centers are isolated by project resource group for good reporting security b00t assumes an agile cadence of releasing early and continuously integration fast fail b00t also is a k8 minimalist recognizing that k8 has a large footprint and creates significant unnecessary complexity for cloud native non legacy applications resource division b00t uses azure landing zone best practice patterns to orchestrate away a considerable amount of complexity in terms of assembling a plurality of well known popular libraries and tools together inside docker containers that then fit into a local inner outer development loop b00t tries not to reinvent the wheel b00t assumes vs code as an integrated environment thus prescribing a suggest list of ide extensions along with a sufficiently pnemonic unique naming approach using ideograms pinyin command glyphs for a variety of tasks such as idea routing error handling storytell mode an emphasis is put on windows development but uses a remote container development environment so it s highly agnostic of individual os choice b00t relies heavily on intellisense and the vs code extension ecosystem especially it s integration with azure for a variety of 1 click tasks c0de b00t presently b00t generally expects to be in c0de b00t ultimately b00t will include internal tooling sufficient to b00t a company or product in a few hours it presumes bash typescript and python environment and also works to some extent on raspberry pi i e no nvidia cuda i intend iot esp32 and arduino functionality in future releases built on top of the b00t template plans to compile a variety of unique reporting summarized using b00t notation to quickly assess project quality code sentiment analysis and identify weak spots presently this is done with tabnine etc what is idempotence determinism the primary preferred pattern for operational code is to operate with as much idempotence isolation as possible also to have the option of both deterministic and non deterministic business application logic https en wikipedia org wiki idempotence idempotence uk d m po t ns 1 us a d m 2 is the property of certain operations in mathematics and computer science whereby they can be applied multiple times without changing the result beyond the initial application a deterministic algorithm is an algorithm which given a particular input will always produce the same output with the underlying machine always passing through the same sequence of states python python severless backend functions with a plurality of messaging socket options for ipc logging azure insight authentication scaffold is azure insight future infrastructure for algorithimic pattern monitoring effectively an ai regression that determines if the code is working typescript vite vue vitesse vitestestee vitestestee http github com elasticdotventures vitestestee is a sample project based on vite vue vitesse openid ms graph ms adslv2 using azure functions and azure logic apps for orchestrating actions which allows a b00t stack to behave as a globally distributed finite state machine this is the higest level of durability which can be assigned to a software platform and is suitable to running fail safe systems such as nuclear reactors the author explicitly disclaims any responsibility for circumstances occurring decide to use b00t to run your own backyard reactor https en wikipedia org wiki deterministic system what is so opionated 0mg b00t tries very hard to be templates and tools tnt but inevitably through the selection of those it s opinions on best approach for example snapd packages are at the core of ubuntu and for various reasons ubuntu is the base image even if you start at alpine linux it s going to look very ubuntu ish if you use b00t the organizational pattern is formatted around a cross competency don t make me think any more than i need to so it assigns emojis to meanings this allows for the system to implement story tell during logs showing entire transactions as a series of pictograms colorful markov chains here is a sample of the projects layout opinion here are the projects opinion hoome b00t your configs your project each project has it s own directory c0de b00t where your projects live project your configs note improve security posture make upper level filesystems readonly and removing configs from lower levels using docker dive files c0de rationale 4 characters 01 start sh start here run this 01 start sh c0de b00t contains the repo put this repo here bash anything in a sh templates bash c0de init sh also the main init script called from 01 start sh dockerfile base docker image standard docker additional docker build files emoji coded c ng layers python python stuff that will probably end up in t00ls node ts typescript libraries c0de cloud azure azure cloud google google cloud still fresh aws aws cloud nothing planned here presently aws aws cloud nothing planned here presently by subscribing to this pattern an effort is made to obviate certain things layers are built upon layers for example a deployed system can be wiped of dockerfiles using rm rf dockerfile docker this is handy at later builds for example a git filesystem can be stripped of utilities that is no longer needed once that is compressed at a docker buildx layer then that information has destroyed during the idempotent container creation tools of b00t git bash jq https stedolan github io jq download yq fzf python node ts docker b00t assumes the author will ultimately decide to end up using a combination of stateful logic so it simplifies the interface to those by creating a unified command language that can be further build on there is a method to the madness i assure you the patterns utilize serverless consumption plans whenever possible the plan is to eventually include complete vs code project files plugin this assumes the developer s are using a three stage release model innerloop local outerloop cloud and or local production live each of those moving the data to the cloud and toward the public no attempts are made want to see examples emoji hsk1 chinese https brianhorakh medium com emoji logging warning much silliness ahead 4cae73d7089 txt c0de b00t this bootstrap code c0de b00t 01 start sh setups up environment c0de b00t 02 project sh create a new project with tooling c0de b00t zz remove sh clean up a project get started note someday soon ish i ll have this as a deploy to azure button working bash for now export resourcegroup newproject export region useast mkdir p c0de cd c0de git clone git github com elasticdotventures b00t git cd b00t 01 start sh that will start running the soon to be interactive installer then once you ve setup b00t you can start to create your own projects to start a new project c0de b00t up new or my project id your project c0de b00t up new my project id b00t will create your project in c0de my project id in the future to upgrade b00t you can simply use git or clone aiia aiia is the tool being built in b00t it s an nlp call center application http elasticdotventures aiia callcenter when finished you ll have a fully integrated development environment with secure language bindings to two languages full permission provision resources with budget friendly serverless consumption models by default to cleanup not finished c0de b00t zz cleanup sh my project id emojis chinese on the cli the author is a hardcore cli guy too for some things using your mouse to copy paste is better since it eliminates fat fingers let s keep it real nobody except absolutely masochists would try to hand type az resource strings so b00t strings are no different you will need to do some cutting and pasting you probably won t like b00t if you re developing on a digital vt100 yeah nah how to move around b00t on the cli you use the cli you re 1337 0k4y hack your brain to use tab complete wildcard shortcuts for directories with emojis or mixed case use wildcards to hit targets so cd c0 will chdir to c0de generally the targets use emoji hsk at the end but as an exercise here s a badly named directory c0de b00t bicep arm azrresmgr could be accessed from it s pwd using any of the following cd command cd bicep cd arm cd azres cd technically this file is misnamed should be bicep arm azrresmgr on windows make sure you re using wsl2 on unbuntu 20 04 with windows terminal preview rather than the default shell and emoji works fine putty and vs terminal both work for outbound ssh and sakura for inbound x term rdp if you re terminal doesn t support emoji switch terminals if you re still using vim you re missing intellisense in vs code and literally every single task is more difficult and error prone tools like azure arm bicep assume vs code intellisense for their transpiler also so no vim emacs support there storytelling in emoji hsk1 chinese i m not gonna here just read my medium https brianhorakh medium com emoji logging warning much silliness ahead 4cae73d7089 b00t what i m building wizard menu cli system engineering poly interface glue of many best practices for anybody that desires a dont make me think more than i need to kiss approach to technical systems engineering accomplished through easy idempotent deterministic meaning predictable container design integration lifecycle a full lifecycle open source systems tool inception creation and deterministic operation from dev to release compliance logging cyber security to exit future https unikraft org | cloud |
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Silver-Tsunami-Analysis | silver tsunami analysis migrate an employee database previously on excel and vba to sql for pewlett hackard a hypothetical technology company and applying data modelling engineering analysis skills on the database to handle an upcoming silver tsunami overview of the silver tsunami analysis bobby is an hr analyst in pewlett hackard as baby boomers are retiring at a rapid pace so we need to help bobby and his manager in the following tasks migrate data in csv format into sql tables determine number of employees retiring per title so that the position can be filled soon determine if a mentorship program can be launched where experienced and successful employees stepping back into a part time role instead of retiring completely their new role in the company would be as a mentor to the newly hired folks look into the current employees to determine if some of them qualify for a mentoring program resources data source departents csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data departments csv dept emp csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data dept emp csv dept manager csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data dept manager csv employees csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data employees csv salaries csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data salaries csv titles csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data titles csv software postgresql x64 11 pgadmin 4 version5 7 silver tsunami analysis results retirement titles table a retirement titles table is created to find the total retiring employees by title by joining employees and titles tables retrieving the emp no first name and last name columns from the employees table and title from date and to date columns from the titles table and joining them both such that only the employees about to retire that i e employees who are born between january 1 1952 and december 31 1955 are included and exported as retirement titles csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data retirement titles csv the first few elements of the queries can be found in retirement titles https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data retirement titles png raw true unique titles table a unique titles table is created to find the the unique employees with their most recent title retrieving the employee number first and last name and title columns from the retirement titles table using distinct on statement to retrieve the first occurrence of the employee number after sorting the table in ascending order by the employee number and descending order by the last date i e to date of the most recent title and exported as unique titles csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data unique titles csv the first few elements of the queries can be found in unique titles https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data unique titles png raw true retiring titles table a retiring titles table is created to find the number of employees retiring with a certain title such that titles having maximum retirees comes first retrieve the number of titles from the unique titles table group the table by title then sort the count column in descending order and exported as retiring titles csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data retiring titles csv the first few elements of the queries can be found in retiring titles https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data retiring titles png raw true mentorship eligibilty table a mentorship eligibilty table is created to find the number of unique employees whose birth dates are between january 1 1965 and december 31 1965 and retireve their emp no first name last name and birth date columns from the employees table retrieve the from date and to date columns from the dept emp table retrieve the title column from the titles table by performing a join with employee dept emp and titles table after filtering the data on the to date column to all the current employees ordering by employee numberand and exporting table as mentorship eligibilty csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data mentorship eligibility csv mentorship eligibilty https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data mentorship eligibilty png raw true the queries executed above and below can be found in employee database challenge https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e queries employee database challenge sql silver tsunami analysis summary a big part of the anlaysis is future proofing the company by determining how many people will be retiring and of those employees who is eligible for a retirement package looking at the retiring titles table we can say that the total number of people born between 1952 and 1955 are 90398 total retirees https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data total retirees png raw true but many of them have already left so they will not account for roles to be filled so the people still working and about to retire are 72458 a emp to retire still working table is created to find the number of unique employees whose birth dates are between january 1 1965 and december 31 1965 still working for ph i e to date 9999 01 01 and retrieve their emp no first name last name title to date columns from the retirement titles table order by emp no and exporting table as emp to retire still working csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data emp to retire still working csv the details of the query can be found in emp to retire still working https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data emp to retire still working png raw true if we count the number of employees in this table we see that the total employees about to retire are 72458 total employees about to retire https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data total employees about to retire png raw true an employees currently working table is created to find the number of unique employees who are still working for ph i e to date 9999 01 01 and retrieve their emp no birth date first name last name gender hire date from employees table and to date columns from the dept emp table and joining them ordering by emp no order by emp no and exporting table as employees currently working csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data employees currently working csv the first few elements of the queries can be found in employees currently working https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data employees currently working png raw true now the total number of employees working currently in pewlett hackard are 240124 total employees currently working https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data total employees currently working png raw true so 72458 employees out of 240124 are born between 1952 and 1955 and may retire soon that is 30 of the workforce that is huge so to know how many roles need to be filled as the silver tsunami begins to make an impact there is a talk about a new mentoring program for employees getting ready to retire instead of having a large chunk of their workforce retiring pewlett hackard wants to introduce a mentoring program experienced and successful employees stepping back into a part time role instead of retiring completely so lets find out are there enough qualified retirement ready employees in the departments to mentor the next generation of pewlett hackard employees a retiring titles still working table is created to find the employee count for each title who will retire soon and may want to be a mentor and retrieve the count of people soon to retire title from the emp to retire still working table grouping them by title ordering by emp no descending and exporting table as retiring titles still working csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data retiring titles still working csv total employee count for each title who will retire soon and may want to be a mentor and enjoy stepping back into a part time role instead of retiring completely to mentor chosen employees who will take their place the details of the query can be found in retiring titles still working https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data retiring titles still working png raw true the dept head of sales and developement showed special interest in knowing how many people in the departments they would need top pitch this idea a emp to retire still working bydept table is created to find the number of unique employees still working with their titles and department names whose birth dates are between january 1 1965 and december 31 1965 and retireve their emp no first name last name title from the emp to retire still working table retrieve the dept no from the dept emp table retrieve the dept name column from the department table by performing a join with emp to retire still working dept emp and department table after ordering by employee number and exporting table as emp to retire still working bydept csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data emp to retire still working bydept csv the first few elements of the queries can be found in emp to retire still working bydept https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data emp to retire still working bydept png raw true to find exactly the employee count by title as well as department as sales or development an emp to retire sales dev table is created to find the employee count for each title with their department name as sales or development who will retire soon and may want to be a mentor and retrieve the count of people soon to retire title dept name from the emp to retire still working bydept table grouping them by dept name title ordering by department name and emp no descending and exporting table as emp to retire sales dev csv https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data emp to retire sales dev csv the details of the query can be found in emp to retire sales dev https github com sucharita1 pewlett hackard analysis blob d9058c288f1e4e441e1b0147c8bf9894291c553e data emp to retire sales dev png raw true | server |
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WebCon-2023 | webcon 2023 six tinkerhubs are coming together to host an amazing web development webinar that you won t want to miss the colleges we represent are namely university college of engineering kariavattom ucek college of engineering trivandrum cet tkm college of engineering kollam college of engineering chengannur cec government college of engineering barton hill gecb and lbs institute of technology for women we believe that every student has the potential to be successful in this field and we are dedicated to helping them reach their full potential | css html html-css-javascript reactjs tailwind-css web webdevelopment | front_end |
Happiness | happiness develop ios 9 app with swift 3 0 stanford university school of engineering 2015 cs193p | os |
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AIR_Drums | view a detailed tutorial tutorial md view video https www youtube com watch v vsih6w8xdue recordit gif images play drums gif augmented reality drums based on concepts of computer vision and image processing a fun application created to enable users to play virtual drums anywhere simply by using colour tags i used hsv based color segmentation method to detect blue color for playing the drum i have used pygames you can use it for entertainment or can learn some key functions of opencv from this code refer a detailed tutorial tutorial md explaining the code air drums py installation clone clone this repo to your local machine using https github com kaustubh sadekar air drums git setup requirements the code is written in python python3 you need the following libraries numpy matplotlib opencv pygame refer the tutorial tutorial md for detailed explaination of the code license license http img shields io license mit blue svg style flat square http badges mit license org mit license http opensource org licenses mit license php | augmented-reality ar opencv-python opencv air-drums tutorial computer-vision color-detection color-spaces hsv-color-detection | ai |
Backway | backway demo application for showing how to use back end way development in qt qml application the technique allows for over the air updates for the ui and business logic which means that it will be downloaded from a server when the application is loaded and updates do not require an update on binary application package in this application only the ui is downloaded over the internet the qml files for the ui are hosted in a server under http zdonik mukhtarov net 8000 selecting the debug configuration in qtcreator will allow to build a felgo live client application for easy development of ui while release configuration let s final application to be built the felgo license key can be inserted as a qmake variable in build steps of qtcreator | server |
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VirtualArena | div align center img src logo jpg width 200 align middle div virtualarena is an object oriented matlab toolkit for control design and system simulation getting started to install the tollkit open matlab on the folder where you want to create the virtualarena folder and run the following code matlab urlwrite https github com andreaalessandretti virtualarena archive master zip master zip unzip master zip movefile virtualarena master virtualarena cd virtualarena addpathsofvirtualarena the folder virtualarena exampels presents a list of examples that are described in the paper alessandretti a aguiar a p jones c n 2017 virtualarena an object oriented matlab toolkit for control system design and simulation in proc of the 2017 international conference on unmanned aircraft systems icuas miami usa docs icuas17 virtualarena pdf and in the slides here docs icuas17 slides pdf the following bibtex entry can be used to cite the toolkit inproceedings alessandretti2017 address miami usa author alessandretti a and aguiar a p and jones c n booktitle proc of the 2017 international conference on unmanned aircraft systems icuas title virtualarena an object oriented matlab toolkit for control system design and simulation year 2017 | os |
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threadx | azure rtos threadx this advanced real time operating system rtos is designed specifically for deeply embedded applications among the multiple benefits it provides are advanced scheduling facilities message passing interrupt management and messaging services azure rtos threadx has many advanced features including picokernel architecture preemption threshold event chaining and a rich set of system services here are the key features and modules of threadx threadx key features docs threadx features png getting started azure rtos has been integrated to the semiconductor s sdks and development environment you can develop using the tools of choice from stmicroelectronics https www st com content st com en campaigns x cube azrtos azure rtos stm32 html nxp https www nxp com design software embedded software azure rtos for nxp microcontrollers azure rtos renesas https github com renesas azure rtos and microchip https mu microchip com get started simplifying your iot design with azure rtos we also provide getting started guide https github com azure rtos getting started and samples https github com azure rtos samples using hero development boards from semiconductors you can build and test with see overview of azure rtos threadx https learn microsoft com en us azure rtos threadx overview threadx for the high level overview and all documentation and apis can be found in azure rtos threadx documentation https learn microsoft com en us azure rtos threadx also there is dedicated learning path of azure rtos threadx https learn microsoft com training paths azure rtos threadx for learning systematically repository structure and usage directory layout cmake cmakelist files for building the project common core threadx files common modules core threadx module files common smp core threadx smp files docs documentation supplements ports architecture and compiler specific files see below for directory breakdown cortex m7 iar example iar compiler sample project example build iar workspace and sample project files inc tx port h for this architecture src source files for this architecture ac6 example ac6 keil sample project gnu example gnu sample project ports modules architecture and compiler specific files for threadx modules ports smp architecture and compiler specific files for threadx smp samples demo threadx c utility test cases and utilities branches releases the master branch has the most recent code with all new features and bug fixes it does not represent the latest general availability ga release of the library each official release preview or ga will be tagged to mark the commit and push it into the github releases tab e g v6 2 rel when you see xx xx xxxx 6 x or x x in function header this means the file is not officially released yet they will be updated in the next release see example below function release tx initialize low level cortex m23 gnu 6 x author scott larson microsoft corporation description this function is responsible for any low level processor initialization including setting up interrupt vectors setting up a periodic timer interrupt source saving the system stack pointer for use in isr processing later and finding the first available ram memory address for tx application define input none output none calls none called by tx initialize kernel enter threadx entry function release history date name description 09 30 2020 scott larson initial version 6 1 xx xx xxxx scott larson include tx user h resulting in version 6 x supported architecture ports threadx arc em cortex a12 cortex m0 cortex r4 arc hs cortex a15 cortex m23 cortex r5 arm11 cortex a17 cortex m3 cortex r7 arm9 cortex a34 cortex m33 c667x cortex a35 cortex m4 linux cortex a5 cortex m55 risc v32 cortex a53 cortex m7 rxv1 cortex a55 cortex m85 rxv2 cortex a57 rxv3 cortex a5x win32 cortex a65 xtensa cortex a65ae cortex a7 cortex a72 cortex a73 cortex a75 cortex a76 cortex a76ae cortex a77 cortex a8 cortex a9 threadx modules azure rtos threadx modules https learn microsoft com azure rtos threadx modules chapter1 component provides an infrastructure for applications to dynamically load modules that are built separately from the resident portion of the application cortex a35 cortex a35 smp cortex a7 cortex m0 cortex m23 cortex m3 cortex m33 cortex m4 cortex m7 cortex r4 rxv2 threadx smp azure rtos threadx smp https learn microsoft com azure rtos threadx threadx smp chapter1 is a high performance real time smp kernel designed specifically for embedded applications arc hs smp cortex a34 smp cortex a35 smp cortex a53 smp cortex a55 smp cortex a57 smp cortex a5x smp cortex a5 smp cortex a65ae smp cortex a65 smp cortex a72 smp cortex a73 smp cortex a75 smp cortex a76ae smp cortex a76 smp cortex a77 smp cortex a78 smp cortex a7 smp cortex a9 smp linux adaptation layer for threadx azure rtos threadx is an advanced real time operating system rtos designed specifically for deeply embedded applications to help ease application migration to azure rtos threadx provides adaption layers https github com azure rtos threadx tree master utility rtos compatibility layers for various legacy rtos apis freertos posix osek etc component dependencies the main components of azure rtos are each provided in their own repository but there are dependencies between them as shown in the following graph this is important to understand when setting up your builds dependency graph docs deps png you will have to take the dependency graph above into account when building anything other than threadx itself building and using the library instruction for building the threadx as static library using arm gnu toolchain and cmake if you are using toolchain and ide from semiconductor you might follow its own instructions to use azure rtos components as explained in the getting started getting started section 1 install the following tools cmake https cmake org download version 3 0 or later arm gnu toolchain for arm none eabi https developer arm com downloads arm gnu toolchain downloads ninja https ninja build org 1 cloning the repo bash git clone https github com azure rtos threadx git 1 define the features and addons you need in tx user h and build together with the component source code you can refer to tx user sample h https github com azure rtos threadx blob master common inc tx user sample h as an example 1 building as a static library each component of azure rtos comes with a composable cmake based build system that supports many different mcus and host systems integrating any of these components into your device app code is as simple as adding a git submodule and then including it in your build using the cmake add subdirectory while the typical usage pattern is to include threadx into your device code source tree to be built linked with your code you can compile this project as a standalone static library to confirm your build is set up correctly an example of building the library for cortex m4 bash cmake bbuild gninja dcmake toolchain file cmake cortex m4 cmake cmake build build professional support professional support plans https azure microsoft com support options are available from microsoft for community support and others see the resources resources section below licensing license terms for using azure rtos are defined in the license txt file of this repo please refer to this file for all definitive licensing information no additional license fees are required for deploying azure rtos on hardware defined in the licensed hardware txt file if you are using hardware not defined in the licensed hardware txt file or have licensing questions in general please contact microsoft directly at https aka ms azrtos license resources the following are references to additional azure rtos resources product introduction and white papers https azure com rtos general technical questions https aka ms qna azure rtos product issues and bugs or feature requests https github com azure rtos threadx issues licensing and sales questions https aka ms azrtos license product roadmap and support policy https aka ms azrtos lts blogs and videos http msiotblog com and https aka ms iotshow azure rtos tracex installer https aka ms azrtos tracex installer you can also check previous questions https stackoverflow com questions tagged azure rtos threadx or ask new ones on stackoverflow using the azure rtos and threadx tags security azure rtos provides oems with components to secure communication and to create code and data isolation using underlying mcu mpu hardware protection mechanisms it is ultimately the responsibility of the device builder to ensure the device fully meets the evolving security requirements associated with its specific use case contribution please follow the instructions provided in the contributing md contributing md for the corresponding repository | embedded iot mcu microcontroller azure-rtos rtos real-time | os |
thainlp | thainlp resources for thai natural language processing see discussions in thai natural language processing fb group https facebook com groups 408004796247683 | ai |
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react-quiz-app | react quiz app develop a quiz application which enables users to take a test of multiple choice questions each question having one correct answer the purpose of this assignment is to create a quiz app which fetches the questions from a remote server allows user to answer questions and submit the assignment on click of submit button once the user submits the answers the system generates a score which is shown to the user on screen use reactjs for frontend development and node js for backend server requirements create a server to do following 1 get a set of questions from server 2 post responses and return the score create an ui to do following 1 retrieve list of questions with options and display the questions options on the page 2 allow user to select answers 3 show results on screen visuals 1 use the provided visuals to create the application base application use create react app good to have 1 only show five questions on page and allow pagination between pages and add a submit button on the last page | server |
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FreeRTOS-TCP-for-PIC32 | freertos tcp for pic32 a freertos tcp port for pic32 microcontrollers project structure cli nbproject fat nbproject include mx 795 mz dab mz ecm mz efm rtos nbproject science nbproject tcpip nbproject requirements to use the source code as is you need one of the following starter kits pic32 ethernet starter kit microchip part no dm320004 pic32mz ec starter kit w crypto engine microchip part no dm320006 c pic32mz embedded connectivity with fpu ef start kit crypto microchip part no dm320007 c pic32mz embedded graphics with external dram da starter kit crypto microchip part no dm320008 c the ethernet module is the same across the pic32 range and this driver has been verified to work on pic32mx795f512l pic32mz2048ecm144 pic32mz2048efm144 and pic32mz2064dab288 the supported ethernet phys include dp83848 lan8740a and lan9303 note the source code should compile and run on the non crypto variants of the pic32mz starter kits but project settings will need to be changed and pic32 has working trng will need to be undefined note the replacement for dm320004 microchip part no dm320004 2 has minimal changes to the circuits but does use a different phy from the original the following software and source code packages are required mplab x ide version 5 40 or later mplab xc32 compiler version 2 41 or later freertos source code version 10 4 0 freertos labs source code version 200218 note there are fixes for freertos tcp and freertos fat that have not been released officially yet see the known issues section for more info non requirements you don t need mplab harmony the microchip legacy peripheral libraries or microchip libraries for applications how to build 1 in the root folder marked in the project structure above you will need to copy unpack the freertos and freertos labs source code alternatively create symbolic links to the locations of the source trees for example on windows mklink d freertos userprofile documents freertos freertos mklink d freertos plus userprofile documents freertos freertos plus mklink d freertos labs userprofile documents freertos labs freertos labs 2 using mplabx ide open the projects cli fat rtos and tcpip 3 for each project select the required configuration and then build the available configurations are mz dab mz efm mz ecm and mx 795 corresponding to the microcontroller type on each starter kit 4 finally load the project called science again select the required configuration and build use the run command in the ide to program the microcontroller known issues a couple of bugs in freertos tcp and freertos fat can result in heap corruption or an exception use unoffical code releases that can be found here https sourceforge net p freertos discussion 382005 thread c27aeb20b5 and also manually apply the modification described here https sourceforge net p freertos discussion 382005 thread 6e3856e518 compiler versions later than v1 44 would sometimes output the assembler code in pic32arch h incorrectly bad register allocations depending on optimisation settings etc this accounts for reports that the driver was not working a modification to the constraints seems to have cured this problem for v2 20 but has only been tested using o0 and o1 the ftp and web server are dependent on freertos fat if you don t need that functionality you can eliminate the dependency by excluding the source files for those components in the tcpip project how to use the program presents a terminal interface via uart2 and a command line interface on tcp port 12345 the pic32 ef starter kit includes a mcp2221 usb to uart converter chip so you can use either interface for the other kits you can only use the tcp cli unless you re willing to add a rs232 interface via the expansion connector the uart terminal interface was mainly used for testing and debugging so there are statistics displays and register dumps which should give you an idea of the sort of things that weren t working at various points in time when the driver began to work it was used for experimentation and investigation the packet test task was used to evaluate performance and latency the leds are toggled at various points in time by using a scope you can get an idea of how the stack and the hardware are performing for example if one starter kit is configured as the transmitter and another as a receiver you can probe led1 on the transmitter to see when the timer interrupt triggered and probe led3 on the receiver to see when the packet arrived the web server and ftp server parts of the freertos tcp demo will also run on the pic32 the web server demo files are stored in a blob containing a fat file system prepared using linux this blob resides in flash and is mounted in www i hacked ff format c to allow the ram disk to be formatted with fat12 this allows a small ram disk to be created that will pass the vcreateandverifyexamplefiles test from the freertos tcp demo the ram disk is mounted in ram this arrangement reduces ram usage considerably and allows the demo to work on the mx class microcontroller too ethernet driver the driver consists of the following files ethernet h ethernet isr s ethernetprivate h networkinterface c phy isr s phygeneric c phygeneric h pic32arch h the freertos tcp configuration defined in freertosipconfig h must contain the following directives for correct operation c define ipconfigzero copy tx driver 1 define ipconfigzero copy rx driver 1 define ipconfiguse linked rx messages 1 define ipconfigdriver included tx ip checksum 0 define ipconfigdriver included rx ip checksum 0 define ipconfigethernet driver filters packets 0 define ipconfigethernet driver filters frame types 1 unless you are using an already supported phy you will need to create a small driver three drivers are provided one for the dp83848 phy used in the mx starter kit one for the lan8740a phy used in the mz starter kits and a simple lan9303 driver note that this implementation assumes the phy interrupt line is connected to the microcontroller to detect link state change events phy support is needed to use wake on lan or the ethernet cable diagnostics only the lan8740a has all of these features all phys allow the interface to be brought up and down powered off the following configuration parameters are available values without defaults must be configured ipconfigpic32 tx dma descriptors number of transmit dma descriptors defaults to 10 ipconfigpic32 rx dma descriptors number of receive dma descriptors defaults to 20 ipconfigpic32 miim management max clk hz maximum mdc clock speed allowed by the phy defaults to 2 5 mhz ipconfigpic32 miim source clock hz for the mz only frequency of t sub pbclk5 sub ipconfigpic32 drv task priority driver task priority ipconfigpic32 drv task stack size driver task stack size in words ipconfigpic32 eth int priority ethernet controller interrupt priority ipconfigpic32 drv task block ticks maximum time the driver waits for stack resources defaults to portmax delay if you want to use one of the built in phy drivers you can set the following configuration parameter ipconfigpic32 phy driver one of pic32 phy driver dp83848 pic32 phy driver lan8740a pic32 phy driver lan9303 the following configuration parameters describe the hardware configuration of your phy ipconfigpic32 phy address phy mii address ipconfigpic32 phy interrupt vector pic32 interrupt vector for the phy interrupt ipconfigpic32 phy assert hw reset optional code to put the phy in reset ipconfigpic32 phy clear hw reset optional code to release the phy from reset ipconfigpic32 phy enable interrupt prepare the pic32 to accept phy interrupts ipconfigpic32 phy disable interrupt mask phy interrupts ipconfigpic32 phy clear interrupt acknowledge the phy interrupt after processing other experiments as well as testing the driver the test harness demonstrates the following additional features wake on lan programmatic ethernet interface up down sram flash wait state configuration for the pic32mx ddr2 controller initialisation for the pic32mz da built in tests march c ram test ethernet loopback ethernet cable diagnostic | freertos pic32 microchip freertos-tcp ethernet-driver | os |
aa | this is a proof of concept website for a small accounting firm it is still in development but the front and backend are both functional the frontend app utilizes react for browser side routing the backend is an express app in communication with a mongodb database the plan is that the website will have a somewhat standard guest presentation with information about the business including services offered and how to contact registered clients will be able to login and view current and or ongoing jobs being handled by the business as well as invoices and any unpaid balances long term the plan is that the business will provide a service that streamlines commissions calculations for insurance companies and their agents | server |
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chulacv2020 | 2110443 computer vision 2020 2 computer vision chulalongkorn university cv2020 assets computer vision is everywhere jpg anaconda download link https www anaconda com download miniconda and miniforge download link https docs conda io en latest miniconda html https github com conda forge miniforge | computer-vision opencv pytorch mmdetection | ai |
llmtools | llmtools run finetune llms on consumer gpus llmtools is a user friendly library for running and finetuning llms in low resource settings features include llm finetuning in 2 bit 3 bit 4 bit precision using the lp lora algorithm easy to use python api for quantization inference and finetuning modular support for multiple llms quantizers and optimization algorithms share all your llms on the huggingface hub llmtools is a research project at cornell university and is based on the following publications jerry chee yaohui cai volodymyr kuleshov christopher de sa quip 2 bit quantization of large language models with guarantees neurips 2023 https arxiv org abs 2307 13304 junjie yin jiahao dong yingheng wang christopher de sa volodymyr kuleshov modulora finetuning 3 bit llms on consumer gpus by integrating with modular quantizers arxiv https arxiv org abs 2309 16119 llmtools implements low precision lora a new memory efficient finetuning algorithm that integrates with an arbitrary quantization module when using the state of the art optq quantizer lp lora can finetune 3 bit llms for the first time see results benchmark below overview llmtools provides an interface similar to the huggingface library for loading generating and finetuning quantized llms python import torch from transformers import autotokenizer from llmtools llms autollm import autollmforcausallm load model and tokenizer model name kuleshov llama 13b 3bit pulls from hf hub llm autollmforcausallm from pretrained model name to cuda tokenizer autotokenizer from pretrained huggyllama llama 13b encode prompt prompt the pyramids were built by input ids tokenizer encode prompt return tensors pt to cuda generate text with torch no grad generated ids llm generate inputs input ids do sample true decode and print output tokenizer decode el item for el in generated ids 0 print output llmtools comes with a patched version of the peft library that can be used to finetune the quantized models using the lp lora method python from transformers import autotokenizer from llmtools llms autollm import autollmforcausallm from llmtools engine lora peft import quant peft load model and tokenizer model name kuleshov llama 13b 3bit pulls from hf hub llm autollmforcausallm from pretrained model name to cuda tokenizer autotokenizer from pretrained huggyllama llama 13b set up finetuning config from llmtools engine lora config import finetuneconfig tune config finetuneconfig set up finetuning config set up lora lora config quant peft loraconfig create a lora config object model quant peft get peft model llm lora config load stanford alpaca data data load the data training args import transformers training arguments transformers trainingarguments set up batch size etc in the usual way start trainer trainer transformers trainer model model train dataset data train data eval dataset data val data args training arguments data collator transformers datacollatorforlanguagemodeling tokenizer mlm false start training trainer train save model model save pretrained tune config lora out dir for more examples of how to perform model quantization inference and finetuning take a look at the examples folder installation requirements llmtools requires a unix environment supporting python 3 8 or greater and pytorch we tested with 1 13 1 cu116 see requirements txt for details to ensure maximum reproducibility consider creating a new conda environment python conda create n llmtools conda activate llmtools conda install git pip virtualenv llmtools also requries an nvidia gpu pascal architecture or newer other platforms are currently unsupported setup we use distutils to package llmtools if you are not running conda you can also create a virtualenv pip install r requirements txt installs torch and two other packages python setup py install installs llmtools in your environment note that this process compiles and installs a custom cuda kernel that is necessary to run quantized models running llmtools download and quantize models first start by downloading the weights of a base llm model currently the llama opt and bloom are supported pre quantized weights can be found here quantized model weights python from llmtools llms autollm import autollmforcausallm model name decapoda research llama 7b hf llm autollmforcausallm from pretrained model name llm eval you can quantize these models within llmtools python from llmtools engine quant config import quantconfig from llmtools engine quant gptq executor import gptqalgorithm from llmtools data calibration import get calibration loaders set up quantization config config quantconfig bits 4 dataset c4 seed 0 nsamples 128 percdamp 01 groupsize 64 act order true nearest false save llama 7b quantized load gptq calibration data dataloader get calibration loaders config dataset nsamples config nsamples seed config seed model llm base model name or path seqlen llm base model seqlen create quantization algorithm gptq gptqalgorithm config llm gptq quantize llm dataloader you can save the quantized model to disk or to the hf hub python llm save pretrained config save print f model weights saved to config save generation next we generate text fron a quantized model we first load the model python import torch from transformers import autotokenizer from llmtools llms autollm import autollmforcausallm load model and tokenizer model name kuleshov llama 13b 3bit pulls from hf hub llm autollmforcausallm from pretrained model name to cuda tokenizer autotokenizer from pretrained huggyllama llama 13b we encode the prompt and generate python encode prompt prompt the pyramids were built by input ids tokenizer encode prompt return tensors pt to cuda generate text with torch no grad generated ids llm generate inputs input ids do sample true decode and print output tokenizer decode el item for el in generated ids 0 print output finetune a base model lastly we can finetune quantized models we again start by loading a model python from transformers import autotokenizer from llmtools llms autollm import autollmforcausallm load model and tokenizer model name kuleshov llama 13b 3bit pulls from hf hub llm autollmforcausallm from pretrained model name to cuda tokenizer autotokenizer from pretrained huggyllama llama 13b we can set parameters via the finetune config object python set up finetuning config from llmtools engine lora config import finetuneconfig tune config finetuneconfig dataset none data type alpaca lora out dir llama 13b quantized lora mbatch size 1 batch size 2 epochs 3 lr 2e 4 cutoff len 256 lora r 8 lora alpha 16 lora dropout 0 05 val set size 0 2 warmup steps 50 save steps 50 save total limit 3 logging steps 10 we instatiate a peft model using our custom patched version of peft python set up lora from llmtools engine lora peft import quant peft lora config quant peft loraconfig r tune config lora r lora alpha tune config lora alpha target modules q proj v proj lora dropout tune config lora dropout bias none task type causal lm model quant peft get peft model llm lora config next we load the finetuning data the library has helpers to pre load common datasets like alpaca python load stanford alpaca data from llmtools data import trainsad data trainsad tune config dataset tune config val set size tokenizer tune config cutoff len data prepare data this tokenizes the dataset the training process is identical to that of standard lora and peft python training args import transformers training arguments transformers trainingarguments per device train batch size tune config mbatch size gradient accumulation steps tune config gradient accumulation steps warmup steps tune config warmup steps num train epochs tune config epochs learning rate tune config lr fp16 true logging steps tune config logging steps evaluation strategy no save strategy steps eval steps none save steps tune config save steps output dir tune config lora out dir save total limit tune config save total limit load best model at end false ddp find unused parameters false if tune config ddp else none start trainer trainer transformers trainer model model train dataset data train data eval dataset data val data args training arguments data collator transformers datacollatorforlanguagemodeling tokenizer mlm false start training trainer train finally we can save and load lora adapters in the usual way python save model model save pretrained tune config lora out dir command line usage you can also use llmtools from the command line first you need to dowload a dataset we currently support the alpaca dataset which we download from the hf hub wget https huggingface co datasets kuleshov alpaca data resolve main dataset json you may now finetune the base llama 65b 4bit model on this dataset mkdir alpaca adapter folder 65b 4bit llmtools finetune model llama 65b 4bit weights llama 65b 4bit pt adapter alpaca adapter folder 65b 4bit dataset dataset json the above command will use lora to finetune the quantized 65b 4 bit model the final adapters and the checkpoints will be saved in alpaca adapter folder 65b 4bit and available for generation as follows llmtools generate model llama 65b 4bit weights llama 65b 4bit pt adapter alpaca adapter folder 65b 4bit instruction write an irrefutable proof that the meaning of life is 42 the llmtools interface provides many additional command line options for finetuning usage llmtools finetune h model llama 7b 4bit llama 13b 4bit llama 30b 4bit llama 65b 4bit opt 6 7b 4bit weights weights data type alpaca gpt4all dataset dataset adapter adapter mbatch size mbatch size batch size batch size epochs epochs lr lr cutoff len cutoff len lora r lora r lora alpha lora alpha lora dropout lora dropout val set size val set size warmup steps warmup steps save steps save steps save total limit save total limit logging steps logging steps resume checkpoint options h help show this help message and exit model llama 7b 4bit llama 13b 4bit llama 30b 4bit llama 65b 4bit opt 6 7b 4bit type of model to load weights weights path to the model weights data type alpaca gpt4all dataset format dataset dataset path to local dataset file adapter adapter path to lora adapter folder also holds checkpoints mbatch size mbatch size micro batch size batch size batch size batch size epochs epochs epochs lr lr learning rate cutoff len cutoff len lora r lora r lora alpha lora alpha lora dropout lora dropout val set size val set size validation set size warmup steps warmup steps save steps save steps save total limit save total limit logging steps logging steps resume checkpoint resume from checkpoint quantized model weights we release our quantized weights for llama model set on hf hub for easy access modulora llama weights 4 bit 3 bit 7b link https huggingface co kuleshov llama 7b 4bit link https huggingface co kuleshov llama 7b 3bit 13b link https huggingface co kuleshov llama 13b 4bit link https huggingface co kuleshov llama 13b 3bit 30b link https huggingface co kuleshov llama 30b 4bit link https huggingface co kuleshov llama 30b 3bit 65b link https huggingface co kuleshov llama 65b 4bit link https huggingface co kuleshov llama 65b 3bit modulora opt weights 4 bit 3 bit 7b link https huggingface co kuleshov opt 6 7b 4bit link https huggingface co kuleshov llama 6 7b 3bit 13b link https huggingface co kuleshov opt 13b 4bit link https huggingface co kuleshov opt 13b 3bit 30b link https huggingface co kuleshov opt 30b 4bit link https huggingface co kuleshov opt 30b 3bit benchmark our method shows competitive performance comparable or superior to baselines and 4bit 8bit bits bytes finetuning by dettmers et al 2023 https arxiv org pdf 2305 14314 on samsum benchmark with the llama touvron et al 2023 https arxiv org pdf 2302 13971 model set 4 bit 65b llama models finetuned with modulora outperform the gpt 3 lora baseline hu et al 2021 https arxiv org abs 2106 09685 and even reach new state of the art performance on this dataset we release complementary codebase modulora experiment https github com kuleshov group modulora experiment to reproduce our results models finetuning adaptation trainable parameters samsum rouge 1 2 l gpt 3 full finetuning 175 255 8m 52 0 28 0 44 5 gpt 3 adapter 40 1m 53 2 29 0 45 1 gpt 3 lora 4 7m 53 8 29 8 45 9 pegasus slic 2b 54 4 29 9 45 9 llama finetuning rouge 1 2 l 7b 13b 30b 65b llmtune 3 bit 51 2 28 2 44 0 52 4 29 6 45 1 53 6 30 8 46 3 54 1 30 9 46 5 llmtune 4 bit 51 7 28 3 44 4 53 2 30 2 46 1 53 9 31 2 46 9 55 9 32 7 49 0 bits bytes 4 bit qlora 51 6 28 3 44 5 51 3 28 1 44 1 53 0 30 2 45 7 53 8 30 5 45 9 bits bytes 8 bit llm int8 51 9 28 1 44 5 51 3 28 2 43 6 50 8 28 4 44 1 53 9 30 4 46 3 hardware requirements the following hardware is needed to run different models in llmtools model size gpu memory requirements compatible gpus 7b 4bit 6gb rtx 2060 3050 3060 13b 4bit 10gb gtx 1080 rtx 2060 3060 3080 30b 4bit 20gb rtx 3080 a5000 3090 4090 v100 65b 4bit 40gb a100 2x3090 2x4090 a40 a6000 only nvidia gpus with the pascal architecture or newer can run the current system examples this is llmtools running an instruction finetuned llama 65b model on one nvidia a6000 llmtools generate model llama 65b 4bit weights llama65b 4bit pt adapter alpaca lora 65b 4bit prompt write a well thought out abstract for a machine learning paper that proves that 42 is the optimal seed for training neural networks the goal of this paper is to prove that 42 is the optimal seed for training neural networks to do so a set of experiments was conducted with various seeds ranging from 0 to 100 for each experiment the neural networks were trained on a standard benchmark dataset and evaluated for accuracy speed of training and generalization accuracy the results were then collected and analyzed the analysis revealed that 42 consistently yielded the highest accuracy with the lowest generalization error as well as the fastest training times furthermore these results were consistent across multiple datasets and neural network architectures based on this evidence it can be concluded that 42 is indeed the optimal seed for training neural networks this paper also discusses the implications of this finding and its potential applications in the field of machine learning in summary this research provides concrete evidence to support the use of 42 as the optimal seed for training neural networks and provides further insights into the optimal parameters for training neural networks in general the findings of this research may have significant implications for the field of machine learning and the development of optimized training strategies for neural networks references 1 x zhang e rashid and t yang an analysis of the optimal seed for training neural networks machine learning journal vol 13 no 1 pp 21 34 2022 2 c kim t smith and a vishwanathan a survey of optimization strategies for training neural networks machine learning journal vol 8 no 4 pp 101 115 2020 3 a krizhevsky i sutskever and g h bradshaw imagenet classification with deep convolutional neural networks j comput vis vol 5 no 3 pp 219 225 2012 in this example the llm produces a recipe for blueberry lasagna llmtools generate model llama 65b 4bit weights llama 65b 4bit pt adapter alpaca lora 65b 4bit e3 instruction write a well thought out recipe for a new blueberry lasagna dish max length 500 ingredients 1 lb lasagna noodles 1 2 cup ricotta cheese 2 eggs 4 tablespoons parmesan cheese 2 cups blueberries 2 tablespoons sugar 2 tablespoons flour 2 tablespoons butter instructions 1 preheat oven to 350 degrees f 2 bring a large pot of salted water to a boil add the lasagna noodles and cook according to package directions 3 in a medium bowl combine the ricotta cheese eggs parmesan cheese and 1 tablespoon of the flour mix until combined 4 in a skillet over medium high heat melt the butter and add the blueberries and sugar cook for 5 minutes stirring occasionally 5 spread a layer of sauce in the bottom of a 9x13 inch baking dish layer with a single layer of lasagna noodles spread the ricotta mixture over the noodles and then layer with the blueberry mixture and another layer of noodles top with remaining parmesan cheese 6 bake for 25 minutes until cheese is melted and bubbly enjoy note you can make the ricotta mixture ahead of time and store it in the fridge you can also cook the blueberry mixture ahead of time and store it in the fridge both should be reheated before assembling the lasagna enjoy the 30b and 65b parameter models can do zero shot chain of thought reasoning i e let s think step by step llmtools generate model llama 65b 4bit weights share kuleshov vk379 llama 65b 4bit pt prompt q roger has 5 tennis balls he buys 2 more cans of tennis balls each can has 3 tennis balls how many tennis balls does he have now a let s think step by step loading llama model done q roger has 5 tennis balls he buys 2 more cans of tennis balls each can has 3 tennis balls how many tennis balls does he have now a let s think step by step roger has 5 balls roger bought 2 cans each can has 3 balls so roger has 5 2 x 3 11 balls now todos this is experimental work in progress work that stills needs to be done out of the box support for additional llms integration with additional quantizers acknowledgements llmtools is based on the following projects the gptq algorithm and codebase by the ist daslab https github com ist daslab gptq with modifications by qwopqwop200 https github com qwopqwop200 the alpaca lora 4bit repo by johnsmith0031 https github com johnsmith0031 the peft repo and its implementation of lora the llama opt and bloom models by meta fair and the bigscience consortium citations please cite this repository if you use our code misc llmtools author volodymyr kuleshov title llmtools fine tuning large language models on one consumer gpu year 2023 publisher github journal github repository howpublished url https github com kuleshov group llmtools we also recommend you cite the above projects on which this work is based feedback please send feedback to volodymyr kuleshov https twitter com volokuleshov | ai |
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LLMMaps | llmmaps a visual metaphor for stratified evaluation of large language models our paper on arxiv https arxiv org abs 2304 00457 llmmap of the performance of chatgpt on the pubmedqa dataset chatgpt pubmedqa svg chatgpt performance on pubmedqa below we show how to use llmmaps for visualization and how to get a raw qa dataset ready for visualization we provide the processed datasets in the data directory to reproduce all visualizations in our paper these do not contain the original question and answer data but everything necessary for the visualization the visualization uses the roboto condensed to be displayed correctly you need it installed all required python packages are listed in requirements txt visualize imported and processed data first we show our visualization pipeline with the process to transform raw data given below for the visualization to work we need the qar qaa and hir files for the respective datasets and models we want to visualize to exist in the data directory and expect the naming convention which results from our other scripts then we pass only the model names and dataset names to tree vis py in the visualization directory all filenames are build from these an example for this and chatgpt on pubmedqa is python3 tree vis py llm models chatgpt datasets pubmedqa draw qna samples max num stacked leafs 9 layer width 420 qna sample quality high and an example case for multiple models on sciq would be python3 tree vis py llm models chatgpt davinci bloom gpt2 llama13b datasets sciq draw qna samples max num stacked leafs 9 layer width 250 qna sample quality high the other figures from our paper could be reproduced with python3 tree vis py llm models chatgpt datasets medmcqa draw qna samples max num stacked leafs 4 layer width 450 qna sample quality high python3 tree vis py llm models chatgpt datasets usbar draw qna samples max num stacked leafs 15 layer width 320 qna sample quality high python3 tree vis py llm models together bloom together gpt j 6b together gpt neox 20b together opt 66b together opt 175b datasets wikifact mmlu naturalqa openbookqa draw qna samples max num stacked leafs 10 layer width 210 qna sample quality high controlling the visualization while the default parameters in tree vis py suffice for obtaining an appealing and informative visualization there are several parameters to control the setup of the resulting mindmap and it s content useful e g if you need to meet figure constraints for a publication also affecting the computation speed the first two arguments control the display of sample population in the stratified knowledge fields the most compute intensive part of the visualization is obtaining the blue noise samples so draw qna samples turns the point sampling and display on which is turned off per default in addition qna sample quality controls the sample size in point relaxation and thus the blue noise quality os the resulting point sample setting this to high assures a good blue noise character of the resulting sample but is also slow the code checks the parameter only for high and not high draw empty leaves controls the display of stratified knowledge fields in which none of the samples could be assorted as this is usually a rather large fraction thus extending vertical size of the resulting figure it is not done per default but can give insights to missing samples covering certain subfields when analyzing the model performance to understand it s accuracy in a specific field layer width controls the widht of each depth level thus affecting horizontal size of the resulting figure lastly max num stacked leafs sets the number of child nodes for each given parent node which should be stacked vertically before starting horizontal stacking thus trading off between vertical and horizontal figure size importing own q a datasets first the q a datasets we want to view needs to be formatted into our data format apart from import qa py all script utilize chatgpt thus you need a valid openai api token and set it in the top of each script for this simply go to data processing and call import qa py for the dataset in question for pubmedqa this would be python3 import qa py path path to pubmedqa data ori pqal json target pubmedqa in general import qa py is the only place to adapt when you want to incorporate new datasets the path argument needs to be supplied only for datasets on a local drive the target argument is required as it controls the cases in import qa py it also is used as the target filename an additional optional argument is from helm this has to be provided to load respective datasets from the helm library needs to exist locally python3 import qa py path path containing helm files target mmlu from helm the separation is made as this will also generate the hir and qaa files since helm already provides many results the results will be imported for a set of picked models these are set to be the ones with results for all datasets we imported bun can simply be changed thus only the difficulty and bloom s taxonomy need to be obtained for the helm data later with the imported data we need to generate the knowledge hierarchy depending on existing knowledge target depth of the knowledge tree and desired procedure we provide different methods in generate hierarchy these are controlled by the method argument for the pubmedqa example this looks like python3 generate hierarchy py path data pubmedqa qar method from topic as we want to visualize also the difficult rating and bloom s taxonomy we have to obtain both this is done with access difficulty py again for the pubmedqa example python3 access difficulty py path data pubmedqa qar lastly we need the answers to all questions and their respective accuracy for this we call get answers py for the pubmedqa example this is python3 get answer py path pubmedqa qar fewshot model chatgpt the models we currently support in this are chatgpt gpt 3 5 turbo non free davinci text davinci 003 non free bloom bloom full model remote huggingface server free gpt2 gpt2 weights from huggingface llama13b llama 13b variant weights from huggingface incorporating other llms in order to incorporate new llm models to the analysis you need to modify get answers py to use additional models these changes need to be made then only concern the process of getting a response for a given inquiry add a new case in answermachine import and answermachine get response the easiest way to achieve this is just copying an existing case and changing the code to get model response for openai and huggingface models this is usually not more than changing the modelname when another llm should also be used for all parts of the knowledge stratification you will also need to adapt access difficulty py and generate hierarchy py to use the different model as we used chatgpt for this the changes to use another openai model are again miniscule using existing data stratification some datasets come with an existing data stratification which can be used for the knowledge visualization with llmmaps an example for this are the fields and given dificulty ratings of the us bar dataset in order to do this the respective labelling has to be transformed into our hir data format as shown with usbargiven hir with the resulting visualization shown below llmmap of the performance of chatgpt on the us bar dataset chatgpt usbargiven svg chatgpt performance on us bar | ai |
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Machine-Learning-Projects | machine learning projects machine learning experiments and work | ai |
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drone-ui | drone ui getting started 1 clone this repository bash git clone https github com drone drone ui git 2 install dependencies bash npm install 3 copy env example and rename it into env bash cp env example env development local 4 fill required variables for example text react app drone server https drone company com react app drone token your drone token find your token in your drone account settings click your avatar in the ui run the app in development mode with hot reloading bash npm run start build the app bash npm run build run the built app bash npm run serve run linters bash npm run lint run linters and fix auto fixable problems bash npm run lint fix run your tests bash npm run test commits we use conventional commits for commit messages you can read more about conventional commits here https www conventionalcommits org en v1 0 0 here https cheatography com albelop cheat sheets conventional commits you can find a useful conventional commits cheat sheet we try to make our commits atomic here https www freshconsulting com atomic commits and here https en wikipedia org wiki atomic commit you can read more about atomic commits release procedure run the changelog generator bash docker run it rm v pwd usr local src your app githubchangeloggenerator github changelog generator u drone p drone ui t secret github token you can generate a token by logging into your github account and going to settings personal access tokens next we tag the pr s with the fixes or enhancements labels if the pr does not fulfil the requirements do not add a label run the changelog generator again with the future version according to semver bash docker run it rm v pwd usr local src your app githubchangeloggenerator github changelog generator u drone p drone ui t secret token future release v1 0 0 update the version in the package json file bash name drone ui react version 2 8 2 update the version here private true scripts build the app and run go generate bash npm run build change to the dist directory cd dist run go generate go111module off go generate this will update the dist dist gen go file create the pull request for the release make sure you have updated and added the following files package json changelog md dist dist gen go look here for an example https github com drone drone ui pull 420 release the new version once your pr is reviewed and merged you can release the new version of the main branch in github please reference the updated changelog in your pr to update drone with the latest ui sha community and support harness community slack https join slack com t harnesscommunity shared invite zt y4hdqh7p rvueqyil5hcx4ck8vcvzbw join the drone slack channel to connect with our engineers and other users running drone ci harness community forum https community harness io ask questions find answers and help other users report a bug https community harness io c bugs 17 find a bug please report in our forum under drone bugs please provide screenshots and steps to reproduce events https www meetup com harness keep up to date with drone events and check out previous events here https www youtube com watch v oq34imugcha list plxsyhfslmqf3zwelqdakovnmleqcvsd9o | front_end |
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davidl | yet another front end dev website https archive davidl fr netlify status https api netlify com api v1 badges ba1747eb b02b 4ee6 b778 3bd080ba695f deploy status https app netlify com sites davidl deploys handcrafted with middleman http middlemanapp com codeless https github com flexbox codeless template author twitter flexbox https gravatar com avatar 66ecc55f1bc2e5863eb516ee6f20794e s 70 https twitter com flexbox follow flexbox on twitter david leuliette https archive davidl fr | middleman sass foundation html markdown github-pages ruby static-site | front_end |
Cloud | cloud cloud engineering activities creation of user and group below are the screenshots of commands used shot1 https github com jidejj cloud assets 9843012 df810990 3545 4c87 996b 2fae9c3f055d shot2 https github com jidejj cloud assets 9843012 c28b15e3 70ea 4124 be32 a3ca6f2bf1d6 shot3 https github com jidejj cloud assets 9843012 da3c2f3d 7464 48c9 9b52 3a040d7a00ab shot4 https github com jidejj cloud assets 9843012 e9efcdf9 7b72 4618 803a 26b0513358e8 operators in bash scripting test operators in bash scripting bash supports the following comparison operators eq equal to ne not equal to lt less than le less than or equal to gt greater than ge greater than or equal to operator description example checks if the value of two operands are equal or not if yes then the condition becomes true a b is not true checks if the value of two operands are equal or not if values are not equal then the condition becomes true a b is true z checks if the given string operand size is zero if it is zero length then it returns true z a is not true n checks if the given string operand size is non zero if it is nonzero length then it returns true n a is not false str checks if str is not the empty string if it is empty then it returns false a is not false we have a few operators that can be used to test various properties associated with a unix file assume a variable file holds an existing file name test the size of which is 100 bytes and has read write and execute permission on operator description example b file checks if file is a block special file if yes then the condition becomes true b file is false c file checks if file is a character special file if yes then the condition becomes true c file is false d file checks if file is a directory if yes then the condition becomes true d file is not true f file checks if file is an ordinary file as opposed to a directory or special file if yes then the condition becomes true f file is true g file checks if file has its set group id sgid bit set if yes then the condition becomes true g file is false k file checks if file has its sticky bit set if yes then the condition becomes true k file is false p file checks if file is a named pipe if yes then the condition becomes true p file is false t file checks if file descriptor is open and associated with a terminal if yes then the condition becomes true t file is false u file checks if file has its set user id suid bit set if yes then the condition becomes true u file is false r file checks if file is readable if yes then the condition becomes true r file is true w file checks if file is writable if yes then the condition becomes true w file is true x file checks if file is executable if yes then the condition becomes true x file is true s file checks if file has size greater than 0 if yes then condition becomes true s file is true e file checks if file exists is true even if file is a directory but exists e file is true l file checks if file is a link if yes then the condition becomes true l file is not true s file checks if file is a socket if yes then the condition becomes true s file is not true | cloud |
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full-stack-web-development | full stack web development in the cloud this repository contains the source code for the full stack web development in the cloud https youtu be ouzauj3geug course architecture the diagram below outlines the high level architecture and the hosting providers for the web application api and database image https user images githubusercontent com 788827 145879564 e7dc42d6 3055 492b 95d7 902e9a5fad96 png ephemeral developer environments the entire course is developed using gitpod https www gitpod io for each task we use an ephemeral developer environment that we dispose of as soon as the task is completed environments are fully automated and we never run npm install or npm run dev manually we also don t have any code dependencies etc installed locally technology stack the course leverages the following technologies web application svelte https svelte dev is a compiler to develop highly performant web applications with great developer experience the application is styled with plain css api sveltekit https kit svelte dev is the library application framework powered by svelte it provides routing server side rendering and also enables us to develop a web application that works if javascript is disabled prisma https www prisma io is the object relational mapping orm library that let s us interact with the database based on models we define prisma generates the database schema and keeps the databsae in sync with our model s in addition it generates a typescript client we import into our code so that we have type safety when we work with database objects database postgres https www postgresql org is our database of choice for the course however thanks to prisma s support for various other databases it is a matter of changing configuration values to leverage a different database deployment the web application and api are hosted on vercel https vercel com whereas the database lives on railway https railway app pull requests each section of the course has a corresponding pull request https github com gitpod io full stack web development pulls q is 3apr is 3aclosed if you get stuck make sure you check out the source code to copy paste what you need | front_end |
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aucs-web-dev | aucs web dev web application development | front_end |
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iot-curriculum | azure iot curriculum github license https img shields io github license microsoft iot curriculum https github com microsoft iot curriculum blob main license github contributors https img shields io github contributors microsoft iot curriculum svg https github com microsoft iot curriculum graphs contributors github issues https img shields io github issues microsoft iot curriculum svg https github com microsoft iot curriculum issues github pull requests https img shields io github issues pr microsoft iot curriculum svg https github com microsoft iot curriculum pull prs welcome https img shields io badge prs welcome brightgreen svg http makeapullrequest com github watchers https img shields io github watchers microsoft iot curriculum svg style social label watch maxage 2592000 https github com microsoft iot curriculum watchers github forks https img shields io github forks microsoft iot curriculum svg style social label fork maxage 2592000 https github com microsoft iot curriculum network github stars https img shields io github stars microsoft iot curriculum svg style social label star maxage 2592000 https github com microsoft iot curriculum stargazers this repo is actively developed watch star or check back often for updates this repo contains hands on labs and other lab and workshop based material designed to support the creation of iot curricula for higher education covering iot and ai on the edge all the labs use physical devices such as raspberry pis and nvidia jetson boards and are designed for in class or at home study as an educator you would use these labs in a blended learning environment teaching concepts and theory in the classroom mixed with labs from here to supplement the course and provide hands on experience most of the content here is microsoft content available in other places this repo brings some of the content together and provides a single place to find content across different github repos documentation microsoft learn and other sites all the content contained in this repo is free for you to use in your courses however you see fit we will endeavour to keep the content up to date but seeing as technology moves fast things may be missed if you find any errors in these materials please either raise an issue https github com microsoft iot curriculum issues or feel free to raise a pr with the fix https github com microsoft iot curriculum pulls we will be continually adding and updating the content here if there is a particular lab or content you would like added please raise an issue https github com microsoft iot curriculum issues if you have content you would like to share please raise a pr https github com microsoft iot curriculum pulls iot for beginners iot for beginners logo https github com microsoft iot for beginners raw main images iot for beginners png https aka ms iot beginners if you are after beginner iot content check out iot for beginners https aka ms iot beginners a 12 week 24 lesson curriculum that teaches iot from the basics each lesson includes pre and post lesson quizzes written instructions to complete the lesson a solution an assignment and more our project based pedagogy allows you to learn while building a proven way for new skills to stick the projects cover the journey of food from farm to table this includes farming logistics manufacturing retail and consumer all popular industry areas for iot devices hardware needs these labs make use of a variety of hardware all connected to cloud services each lab indicates up front what hardware is required there is also an overall list for an iot cart that provides a complete all in one hardware solution that covers all these labs this is designed to be a course in a box you purchase everything on the list and that can be shared between groups of students learning iot in a more iot focused degree program rather than a single course as part of a wider technology based learning program details of the cart are in the cart cart folder device setup the devices devices folder contains details on setting up the different devices recommended for the iot cart labs the labs labs folder contains details on a range of different labs covering iot and ai on the edge educator guides the educator guides educator guides folder contains guides for educators including suggested course outlines and iot lab guides microsoft learn microsoft learn https docs microsoft com learn wt mc id academic 7372 jabenn is a free online training platform that provides interactive learning for microsoft products and more our goal is to help you become proficient on our technologies and learn more skills with fun guided hands on interactive content that s specific to your role and goals there are a number of learning paths covering iot technologies services and solutions these can form a hands on component of a blended learning setup in the classroom or provide a way for students to learn by themselves fundamentals azure fundamentals https docs microsoft com learn paths azure fundamentals wt mc id academic 7372 jabenn introduction to internet of things https docs microsoft com learn paths introduction to azure iot wt mc id academic 7372 jabenn build the intelligent edge with azure iot edge https docs microsoft com learn paths build intelligent edge with azure iot edge wt mc id academic 7372 jabenn architect api integration in azure https docs microsoft com learn paths architect api integration wt mc id academic 7372 jabenn microsoft power platform fundamentals https docs microsoft com learn paths power plat fundamentals wt mc id academic 7372 jabenn iot10 connecting your physical environment to a digital world a roadmap to iot solutioning https aka ms iot10 resources iot concepts and services introduction to azure iot hub https docs microsoft com learn modules introduction to iot hub wt mc id academic 7372 jabenn securely connect iot devices to the cloud https docs microsoft com learn paths securely connect iot devices wt mc id academic 7372 jabenn develop iot solutions with azure iot central https docs microsoft com learn paths develop iot solutions with azure iot central wt mc id academic 7372 jabenn iot20 deciphering data optimizing data communication to maximize your roi https aka ms iot20 resources develop with azure digital twins https docs microsoft com learn paths develop azure digital twins wt mc id academic 7372 jabenn data create and use analytics reports with power bi https docs microsoft com learn paths create use analytics reports power bi wt mc id academic 7372 jabenn azure for the data engineer https docs microsoft com learn paths azure for the data engineer wt mc id academic 7372 jabenn architect a data platform in azure https docs microsoft com learn paths architect data platform wt mc id academic 7372 jabenn implement a data warehouse with azure synapse analytics https docs microsoft com learn paths implement sql data warehouse wt mc id academic 7372 jabenn azure data fundamentals explore core data concepts https docs microsoft com learn paths azure data fundamentals explore core data concepts wt mc id academic 7372 jabenn data engineering with azure databricks https docs microsoft com learn paths data engineer azure databricks wt mc id academic 7372 jabenn iot40 big data 2 0 iot as your new operational data source https aka ms iot40 resources ai and machine learning ai edge engineer https docs microsoft com learn paths ai edge engineer wt mc id academic 7372 jabenn create machine learning models https docs microsoft com learn paths create machine learn models wt mc id academic 7372 jabenn create no code predictive models with azure machine learning https docs microsoft com learn paths create no code predictive models azure machine learning wt mc id academic 7372 jabenn ai business school for manufacturing https docs microsoft com learn paths ai business school manufacturing wt mc id academic 7372 jabenn get started with artificial intelligence on azure https docs microsoft com learn paths get started with artificial intelligence on azure wt mc id academic 7372 jabenn microsoft azure artificial intelligence ai strategy and solutions https docs microsoft com learn modules azure artificial intelligence wt mc id academic 7372 jabenn build ai solutions with azure machine learning https docs microsoft com learn paths build ai solutions with azure ml service wt mc id academic 7372 jabenn explore computer vision in microsoft azure https docs microsoft com learn paths explore computer vision microsoft azure wt mc id academic 7372 jabenn process and classify images with the azure cognitive vision services https docs microsoft com learn paths classify images with vision services wt mc id academic 7372 jabenn explore natural language processing https docs microsoft com learn paths explore natural language processing wt mc id academic 7372 jabenn process and translate speech with azure cognitive speech services https docs microsoft com learn paths process translate speech azure cognitive speech services wt mc id academic 7372 jabenn evaluate text with azure cognitive language services https docs microsoft com learn paths evaluate text with language services wt mc id academic 7372 jabenn bring ai to business users in your organization https docs microsoft com learn paths bring ai to business users your organization wt mc id academic 7372 jabenn iot30 adding intelligence unlocking new insights with ai machine learning https aka ms iot30 resources iot scenarios iot demos https github com azure samples iotdemos examples of end to end use cases and the iot architectures that enable to those use cases configure and manage products and inventory in dynamics 365 supply chain management https docs microsoft com learn paths configure manage products inventory dyn365 supply chain mgmt wt mc id academic 7372 jabenn configure and use lean manufacturing in dynamics 365 supply chain management https docs microsoft com learn paths configure use lean manufacturing dyn365 supply chain mgmt wt mc id academic 7372 jabenn configure and use discrete manufacturing in dynamics 365 supply chain management https docs microsoft com learn paths configure use discrete manufacturing dyn365 supply chain mgmt wt mc id academic 7372 jabenn iot50 get to solutioning strategy best practices when mapping designs from edge to cloud https aka ms iot50 resources iot videos microsoft iot developers channel on youtube https www youtube com channel ucl7wy iy v76xxpnrizgozq watch latest videos about microsoft iot updates and news partners and customers spotlights interactive deep dives as well as demos the iot show on channel9 https channel9 msdn com shows internet of things show wt mc id academic 7372 jabenn the latest microsoft iot announcements product and features demos customer and partner spotlights top industry talks and technical deep dives maker show https youtube com playlist list plfi bhzy0z5r fdcy3es4se1ucyi4r ih a maker and iot focused show from the fordevs community iot 101 with net on channel9 https channel9 msdn com series iot 101 wt mc id academic 7372 jabenn a 101 level video series to learn iot on net solution quickstarts microsoft offers a number of solution accelerators almost complete iot setups that can be customized to your needs as a part of this there are a number of quickstarts that allow you to try out the different solutions try a cloud based remote monitoring solution https docs microsoft com azure iot accelerators quickstart remote monitoring deploy wt mc id academic 7372 jabenn try a cloud based solution to manage my industrial iot devices https docs microsoft com azure iot accelerators quickstart connected factory deploy wt mc id academic 7372 jabenn deploy and run an iot device simulation in azure https docs microsoft com azure iot accelerators quickstart device simulation deploy wt mc id academic 7372 jabenn try a cloud based solution to run a predictive maintenance analysis on my connected devices https docs microsoft com azure iot accelerators quickstart predictive maintenance deploy wt mc id academic 7372 jabenn reference architectures the azure architecture center https docs microsoft com azure architecture wt mc id academic 7372 jabenn provides guidance for architecting solutions on azure using established patterns and practices azure iot reference architecture https docs microsoft com azure architecture reference architectures iot wt mc id academic 7372 jabenn iot and data analytics in the construction industry https docs microsoft com azure architecture example scenario data big data with iot wt mc id academic 7372 jabenn controlling iot devices using a voice assistant https docs microsoft com azure architecture solution ideas articles iot devices wt mc id academic 7372 jabenn iot using cosmos db https docs microsoft com azure architecture solution ideas articles iot using cosmos db wt mc id academic 7372 jabenn iot connected platform for covid 19 protection https docs microsoft com azure architecture solution ideas articles iot connected platform wt mc id academic 7372 jabenn contactless interfaces with azure iot edge https docs microsoft com azure architecture solution ideas articles contactless interfaces wt mc id academic 7372 jabenn covid 19 safe solutions at the iot edge https docs microsoft com azure architecture solution ideas articles cctv mask detection wt mc id academic 7372 jabenn smart and secure lighting and disinfection https docs microsoft com azure architecture solution ideas articles uven disinfection wt mc id academic 7372 jabenn predictive maintenance with the intelligent iot edge https docs microsoft com azure architecture example scenario predictive maintenance iot predictive maintenance wt mc id academic 7372 jabenn ingestion and processing of real time automotive iot data https docs microsoft com azure architecture example scenario data realtime analytics vehicle iot wt mc id academic 7372 jabenn create a safe building https docs microsoft com azure architecture solution ideas articles safe buildings wt mc id academic 7372 jabenn secure your iot saas app with the microsoft identity platform https docs microsoft com azure architecture example scenario iot aad iot aad wt mc id academic 7372 jabenn azure industrial iot analytics guidance https docs microsoft com azure architecture guide iiot guidance iiot architecture wt mc id academic 7372 jabenn industrial iot for industrial iot iiot microsoft provides a range of reference materials and samples based around opc ua iiot on azure documentation https docs microsoft com azure iot accelerators overview iot industrial wt mc id academic 7372 jabenn documentation and a solution accelerator for iiot open62541 https github com open62541 open62541 an open source opc ua implementation opc ua with iot central https github com jlorich demo opc iot edge to central a reference implementation for connecting opc servers to iot edge and then passing data up to iot central iot edge offline dashboarding https github com azureiotgbb iot edge offline dashboarding a set of modules that can be used with azure iot edge to perform dashboarding at the edge digital agriculture farmbeats https www microsoft com research project farmbeats iot agriculture wt mc id academic 7372 jabenn ai edge iot for agriculture farmbeats for students lesson plans https education microsoft com lesson 5d991297 wt mc id academic 7372 jabenn a program combining an affordable hardware kit with curriculum and activities designed to give students hands on experience in applying precision agriculture techniques to food production farmbeats for students videos on youtube https www youtube com playlist list pldi jxfb4oodbxrr2w2cu0vx8jzwgvu6k digital twins develop with azure digital twins learning path on microsoft learn https docs microsoft com learn paths develop azure digital twins wt mc id academic 7372 jabenn digital twins hands on lab https github com azure samples digital twins samples tree master handsonlab robotics robot operating system ros with windows 10 linux and azure https microsoft github io win ros landing page azure rtos azure rtos is an embedded development suite including a small but powerful operating system that provides reliable ultra fast performance for resource constrained devices it s easy to use and market proven having been deployed on more than 6 2 billion devices worldwide azure rtos supports the most popular 32 bit microcontrollers and embedded development tools so you can make the most of your team s existing skills overview of azure rtos https azure microsoft com services rtos wt mc id academic 7372 jabenn azure rtos on github https github com azure rtos introduction to azure rtos video on channel9 https channel9 msdn com shows internet of things show introduction to azure rtos wt mc id academic 7372 jabenn programming languages platforms and tools there are many different programming languages platforms and tools you can use for iot here are some language resources python python is a popular language for developing iot solutions on devices such as the raspberry pi it s also popular for data science and building machine learning models to analyze the data coming from iot devices azure python iot sdk https github com azure azure iot sdk python this repository contains code for the azure iot sdks for python this enables python developers to quickly create iot device solutions that seamlessly connect to the azure iothub ecosystem python for beginners video series on channel9 https channel9 msdn com series intro to python development wt mc id academic 7372 jabenn over the course of a set of videos we re going to show you the ropes of python development more python for beginners video series on channel9 https channel9 msdn com series more python for beginners wt mc id academic 7372 jabenn more python for beginners videos take your first steps with python learning path on microsoft learn https docs microsoft com learn paths python first steps wt mc id academic 7372 jabenn interested in learning a programming language but aren t sure where to start start here learn the basic syntax and thought processes required to build simple applications using python circuitpython azure iot sdk https github com adafruit adafruit circuitpython azureiot an azure iot sdk for use with adafruit circuitpython https circuitpython readthedocs io a variant of python for embedded devices net net is a free cross platform open source developer platform for building applications and supports programming languages such as c and f azure iot c sdk https github com azure azure iot sdk csharp a c sdk for connecting to azure iot services net home page https dotnet microsoft com wt mc id academic 7372 jabenn the home of net net 101 video series https dotnet microsoft com learn videos wt mc id academic 7372 jabenn a 101 level video series to learn net iot 101 on channel9 https channel9 msdn com series iot 101 wt mc id academic 7372 jabenn a 101 level video series to learn iot on net net for iot devices https github com dotnet iot this repo includes net core implementations for various iot boards chips displays and pcbs c c azure iot c sdk https github com azure azure iot sdk c a c sdk for connecting to azure iot services javascript node js azure iot node sdk https github com azure azure iot sdk node the azure iot node js sdk enables developers to create iot solutions written in node js for the azure iot platform beginner s series to javascript https channel9 msdn com series beginners series to javascript wt mc id academic 7372 jabenn a series of practical bite sized videos about javascript for beginners so you can get up to speed quickly beginner s series to node js https channel9 msdn com series beginners series to nodejs wt mc id academic 7372 jabenn a series of practical bite sized videos about node js for beginners so you can get up to speed quickly arduino azure iot hub library for arduino https github com azure azure iot arduino this library is a port of the microsoft azure iot device sdk for c to arduino it allows you to use several arduino compatible boards with azure iot hub visual studio code visual studio code vs code is a free open source cross platform developer text editor that can be extended by a huge range of extensions to support different programing languages and capabilities visual studio code http code visualstudio com wt mc id academic 7372 jabenn the home of vs code platform io https platformio org platformio ide an extension for vs code that provides tools for embedded c c development with no additional dependencies remote developer pack https marketplace visualstudio com items itemname ms vscode remote vscode remote extensionpack wt mc id academic 7372 jabenn an extension to support remote development such as connecting to a raspberry pi and developing on that pi from your pc or mac pylance python language extension https marketplace visualstudio com items itemname ms python vscode pylance wt mc id academic 7372 jabenn an extension providing python language support to vs code c c https marketplace visualstudio com items itemname ms vscode cpptools wt mc id academic 7372 jabenn full intellisense and debugging support for c and c development iot events in a box if you are interested in running an iot event here are some events in a box giving access to event materials such as slide decks video walkthroughs and code samples iot event learning path https github com microsoft internet of things event learning path the internet of things event learning path is designed for solution architects business decision makers and development teams that are interested in building iot solutions with azure services the content is comprised of 5 video based modules that approach topics ranging from iot device connectivity iot data communication strategies use of artificial intelligence at the edge data processing considerations for iot data and iot solutioning based on the azure iot reference architecture azure subscriptions these labs are designed for courses where azure resources are provided to students by the institution to try them out you can use one of our free subscriptions head to the azure subscriptions guide azure subscription md for from information on setting up a subscription get certified microsoft offers a certification in iot az 220 the microsoft certified azure iot developer specialty microsoft certified azure iot developer specialty page on microsoft learn https docs microsoft com learn certifications azure iot developer specialty wt mc id academic 7372 jabenn az 220 microsoft azure iot developer study guide https microsoftlearning github io az 220 microsoft azure iot developer microsoft learn student ambassadors finding your community is more important than ever as classes and social activities take place virtually amplify your impact and bring together your peers to learn new skills solve real world problems and build communities across the globe students can apply to be a microsoft learn student ambassadors the student ambassadors program provides clear steps to help you learn and lead so you can make a difference and empower those around you student ambassadors get access to unique resources like our global student network on microsoft teams and a microsoft 365 account and can earn badges for activities and contributions to unlock additional benefits such as cloud credits if you are an educator encourage your students to sign up for this program to help their peers learn new skills and to improve employability after their studies you can learn more on the microsoft learn student ambassadors site https studentambassadors microsoft com wt mc id academic 7372 jabenn imagine cup reimagine our world with technology in the 2021 imagine cup we re looking for bold thinkers and big dreamers to join the 2021 competition journey make an impact through coding collaboration and competition innovate with passion to tackle global issues and bring your idea to life in the imagine cup the 19th annual imagine cup is more than just a competition for students you can work with friends and make new ones network with professionals gain new skills make a difference in the world and have the chance to win great prizes read more and sign up at imaginecup microsoft com https imaginecup microsoft com wt mc id academic 7372 jabenn contributing this project welcomes contributions and suggestions most contributions require you to agree to a contributor license agreement cla declaring that you have the right to and actually do grant us the rights to use your contribution for details visit https cla opensource microsoft com https cla opensource microsoft com wt mc id academic 7372 jabenn when you submit a pull request a cla bot will automatically determine whether you need to provide a cla and decorate the pr appropriately e g status check comment simply follow the instructions provided by the bot you 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challenges-front-end | womakerscode logotipo https user images githubusercontent com 2198735 80845484 b93d6d80 8bdf 11ea 8f9b c8b48368ba79 jpg front end challenges este reposit rio mantido pela comunidade womakerscode trazendo uma s rie de desafios e tutoriais sobre desenvolvimento front end license https img shields io github license womakerscode challenges front end svg license question n o sabe o que git ou github se voc n o sabe o que git ou github recomendamos que leia este artigo https tableless com br tudo que voce queria saber sobre git e github mas tinha vergonha de perguntar e qualquer d vida voc pode perguntar no canal general do nosso slack thinking como funciona estamos adicionando os desafios na aba issues deste reposit rio todos os desafios est o marcados uma label de n vel de dificuldade j os tutoriais workshops e conte dos extensos ficam em pastas nesse mesmo reposit rio entendendo as labels de n vel level 100 b sico level 200 intermedi rio level 300 avan ado level 400 expert computer desafios dispon veis desafio resolu o n vel formul rio de cep https github com womakerscode challenges front end issues 1 level 300 photogrid https github com womakerscode challenges front end issues 6 level 100 conversor de moedas https github com womakerscode challenges front end issues 11 level 300 formul rio de login responsivo https github com womakerscode challenges front end issues 15 level 200 closed book tutoriais dispon veis tutorial n vel flexbox https github com womakerscode challenges front end tree master tutorial flexbox level 100 d vidas frequentes question tenho uma sugest o de desafio posso colaborar 1 claro que pode crie uma ssue com seu desafio 2 fa a um fork desse reposit rio 3 adicione o link para sua issue na tabela acima de desafios dispon veis 4 envie um pull request tada question n o entendi um enunciado o que eu fa o 1 voc pode interagir nos coment rios da issue enviando a sua d vida 2 entre no slack acesse o canal challenges fronted l tiramos todas as d vidas e auxiliamos no que for poss vel referente a esse reposit rio entre no nosso slack clicando aqui https app slack com client tcpdkmm4z ccq5xkxpx question posso enviar um tutorial para enviar um tutorial siga os seguintes passos 1 fork and knife fa a uma fork deste reposit rio 2 hammer siga o guia de contribui o 3 busts in silhouette adicione o seu perfil na rea de pessoas colaboradoras do projeto contributors 4 wrench envie um pull request 5 tada tenha o seu pull request aprovado sucesso contributors la s lima https twitter com laislima dev kamila santos https twitter com kamilah santos ana beatriz https twitter com anabneri bianca pereira https github com biancapereira aline bezzoco https github com bezzocoaline cynthia zanoni https github com cyz e samara miranda https github com samaramiranda e leticia campos https github com leticiacamposs2 | frontend challenges challenges-solved react hacktoberfest angular vue javascript | front_end |
GCN-Text-Classification | text categorization using gcn inzva ai projects 4 text categorization using gcn showcase cover with photos docs pics showcase cover with photos jpeg abstract our project aims to tackle text classification problem with novel approaches graph convolutional networks and graph attention networks using deep learning algorithms and natural language processing techniques build it is applicable for only linux distros you can update the commands and use the equivalent ones in other distros mac windows etc executing buid sh will create a new virtual environment in the project folder and install dependencies into that run the following command to build bash bash build sh be sure that your computer is connected to internet it can take a while to download and install the dependendencies run available datasets 20ng newsgroup dataset r8 reuters news dataset with 8 labels r52 reuters news dataset with 52 labels ohsumed cardiovascular diseases abstracts dataset mr movie reviews dataset cora citation dataset citeseer citation dataset pubmed citation dataset preprocess bash venv bin python3 preprocess py dataset name example venv bin python3 preprocess py r8 train bash venv bin python3 train py dataset name example venv bin python3 train py r8 contributors berk sudan github https github com berksudan linkedin https linkedin com in berksudan g neykan zg l github https github com guneykan linkedin https www linkedin com in guneykan ozgul example output console python3 preprocess py r8 warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus cleaned already exists not overwritten nltk data downloading package stopwords to venv nltk data nltk data unzipping corpora stopwords zip info cleaned corpus dir home linuxuser desktop gcnn repo gcn text categorization data corpus cleaned info rare count 5 info cleaned data removed rare stop words warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled already exists not overwritten warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled meta already exists not overwritten warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled split index already exists not overwritten info shuffled corpus dir home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled info shuffled data corpus documents shuffled warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled vocabulary already exists not overwritten warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled word vectors already exists not overwritten nltk data downloading package wordnet to venv nltk data nltk data unzipping corpora wordnet zip info vocabulary dir home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled vocabulary info word vector dir home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled word vectors info prepared words vocabulary word vectors extracted warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled node features r8 already exists not overwritten info x shape 4937 300 y shape 4937 8 info tx shape 2189 300 ty shape 2189 8 info allx shape 13173 300 ally shape 13173 8 info extracted node features x y tx ty allx ally warn directory home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled adjacency already exists not overwritten info adjacency dir home linuxuser desktop gcnn repo gcn text categorization data corpus shuffled adjacency info extracted adjacency matrix heterogenous doc word adjacency matrix console python3 train py r8 2020 8 16 19 12 00 epoch 1 train loss 2 10250 train acc 0 04436 val loss 2 06262 val acc 0 62044 time 4 47397 2020 8 16 19 12 02 epoch 2 train loss 1 91917 train acc 0 66235 val loss 2 05057 val acc 0 68978 time 2 37341 2020 8 16 19 12 05 epoch 3 train loss 1 80157 train acc 0 72514 val loss 2 04366 val acc 0 72263 time 2 30123 2020 8 16 19 12 07 epoch 4 train loss 1 73192 train acc 0 76727 val loss 2 03955 val acc 0 75365 time 2 29406 2020 8 16 19 14 40 epoch 61 train loss 1 42440 train acc 0 99149 val loss 2 01033 val acc 0 96350 time 2 95969 2020 8 16 19 14 43 epoch 62 train loss 1 42407 train acc 0 99190 val loss 2 01033 val acc 0 96168 time 2 79453 2020 8 16 19 14 45 epoch 63 train loss 1 42377 train acc 0 99271 val loss 2 01034 val acc 0 96168 time 2 56621 2020 8 16 19 14 45 early stopping 2020 8 16 19 14 45 optimization finished 2020 8 16 19 14 46 test set results 2020 8 16 19 14 46 loss 1 79863 accuracy 0 97076 time 0 85016 2020 8 16 19 14 46 test precision recall and f1 score 2020 8 16 19 14 47 precision recall f1 score support 2020 8 16 19 14 47 2020 8 16 19 14 47 0 0 9826 0 9917 0 9871 1083 2020 8 16 19 14 47 1 0 9706 0 8148 0 8859 81 2020 8 16 19 14 47 2 0 9826 0 9741 0 9784 696 2020 8 16 19 14 47 3 0 9435 0 9669 0 9551 121 2020 8 16 19 14 47 4 0 8454 0 9425 0 8913 87 2020 8 16 19 14 47 5 0 9012 0 9733 0 9359 75 2020 8 16 19 14 47 6 0 9615 0 6944 0 8065 36 2020 8 16 19 14 47 7 1 0000 1 0000 1 0000 10 2020 8 16 19 14 47 2020 8 16 19 14 47 accuracy 0 9708 2189 2020 8 16 19 14 47 macro avg 0 9484 0 9197 0 9300 2189 2020 8 16 19 14 47 weighted avg 0 9715 0 9708 0 9703 2189 2020 8 16 19 14 47 2020 8 16 19 14 47 macro average test precision recall and f1 score 2020 8 16 19 14 47 0 9484369779553932 0 9197363948390138 0 9300186011259608 none 2020 8 16 19 14 47 micro average test precision recall and f1 score 2020 8 16 19 14 48 0 9707629054362723 0 9707629054362723 0 9707629054362723 none 2020 8 16 19 14 48 embeddings word embeddings 7688 train doc embeddings 5485 test doc embeddings 2189 word embeddings 48 0 0 16006473 0 0 23560655 0 03900092 0 03204489 0 77342826 0 0 0 0 5302985 0 6264921 0 7280124 0 2820953 0 0 0 11174901 0 5485109 0 3487121 0 00971795 0 16308378 0 23769674 0 19000074 0 06477314 0 04132688 0 10753749 0 06603149 0 05606151 0 13652363 0 0443929 0 06743763 0 23347118 0 36717737 0 15584956 0 0 references papers liang yao chengsheng mao yuan luo 2018 graph convolutional networks for text classification kipf and welling 2017 semi supervised classification with graph convolutional networks ankit pal 2020 multi label text classification using attention based graph neural network petar velickovic 2017 graph attention networks repos pytorch implementation of graph attention networks https github com diego999 pygat pytorch implementation of graph convolutional networks https github com tkipf pygcn | natural-language-processing graph-neural-networks graph-convolutional-networks pytorch deep-learning python text-classification graph-attention-networks | ai |
job-search-website | h2 align center job search api h2 nodejs expressjs mongodb jwt swagger overview nodejs express project focusing on backend development api for the job applications app see swagger ui rest api for supported operations swagger ui https job applications website v1 bd784586a4a7 herokuapp com api docs can also be hosted using this template https github com peter evans swagger github pages https ayazhankadessova github io job search swagger setup bash npm install npm start rest api use prod url https job applications website v1 bd784586a4a7 herokuapp com or https localhost 3000 1 register a user post api v1 auth register body name yerkezhank email kadessovayerkezhan2 gmail com password yerkekadessova response user name yerkezhank token eyjhbgcioijiuzi1niisinr5cci6ikpxvcj9 eyj1c2vyswqioii2ngy4nwuzyzfjntqzmzawmdi3zdrkyjeilcjuyw1lijoiwwvya2v6agfusyisimlhdci6mty5mzk5ody1miwizxhwijoxnjk2ntkwnjuyfq xyw xwilrrovnhs3qorqqpjjd0prnzhfn5w71l7sptc http 1 1 201 created date thu 7 sep 2023 12 36 30 gmt status 201 ok connection close content type application json content length 2 2 login a user post api v1 auth login body email kadessovayerkezhan2 gmail com password yerkekadessova response user name yerkezhank token eyjhbgcioijiuzi1niisinr5cci6ikpxvcj9 eyj1c2vyswqioii2ngy4nwuzyzfjntqzmzawmdi3zdrkyjeilcjuyw1lijoiwwvya2v6agfusyisimlhdci6mty5mzk5odc0nswizxhwijoxnjk2ntkwnzq1fq plh8kvmklafvntt1btmuesmo7gvxmwgm 10sr2vjyo0 http 1 1 200 ok date thu 7 sep 2023 12 36 30 gmt status 200 ok connection close content type application json content length 2 tests const jsondata pm response json pm globals set accesstoken jsondata token 3 create a job post api v1 jobs auth type bearer token token accesstoken body company pfizer position business solutions analyst response newjob status pending id 64f85f281c543300027d4db7 company pfizer position business solutions analyst 2 createdby 64f85e3c1c543300027d4db1 createdat 2023 09 06t11 14 48 150z updatedat 2023 09 06t11 14 48 150z v 0 http 1 1 201 created date thu 7 sep 2023 12 36 30 gmt status 201 created connection close content type application json content length 2 4 get all jobs get api v1 jobs auth type bearer token token accesstoken response jobs status pending id 64f85eeb1c543300027d4db5 company pfizer position business solutions analyst createdby 64f85e3c1c543300027d4db1 createdat 2023 09 06t11 13 47 665z updatedat 2023 09 06t11 13 47 665z v 0 status pending id 64f85f281c543300027d4db7 company pfizer position business solutions analyst 2 createdby 64f85e3c1c543300027d4db1 createdat 2023 09 06t11 14 48 150z updatedat 2023 09 06t11 14 48 150z v 0 count 2 http 1 1 200 ok date thu 7 sep 2023 12 36 30 gmt status 200 ok connection close content type application json content length 2 5 get single job get api v1 jobs 64f85eeb1c543300027d4db5 auth type bearer token token accesstoken body job status pending id 64f85eeb1c543300027d4db5 company pfizer position business solutions analyst createdby 64f85e3c1c543300027d4db1 createdat 2023 09 06t11 13 47 665z updatedat 2023 09 06t11 13 47 665z v 0 http 1 1 200 ok date thu 7 sep 2023 12 36 30 gmt status 200 ok connection close content type application json content length 2 6 update a job patch api v1 jobs 64f85eeb1c543300027d4db5 auth type bearer token token accesstoken body company pfizer kz position site reliability engineer response job status pending id 64f85eeb1c543300027d4db5 company pfizer kz position site reliability engineer createdby 64f85e3c1c543300027d4db1 createdat 2023 09 06t11 13 47 665z updatedat 2023 09 06t11 18 18 830z v 0 http 1 1 200 ok date thu 7 sep 2023 12 36 30 gmt status 200 ok connection close content type application json content length 2 7 delete a single job delete api v1 jobs 64f85eeb1c543300027d4db5 auth type bearer token token accesstoken step by step workflow 1 bootstrap done 2 add dummy controllers done 3 add routes done 4 check if routes work done 5 connect db works done 6 create user model done email validation regex s s 0 9 1 3 0 9 1 3 0 9 1 3 0 9 1 3 a za z 0 9 a za z 2 add unique indexing for email 7 register route 1 validate name email password with mongoose done 2 hash password with bcryptjs done 3 create token in controller done 4 create token move to schema instance method done 5 generate token for jwt secret set lifetime as env var done 6 send response with token if valid done 8 login router 1 in controller get email password do not need a name done 2 if no email or password throw badrequesterror done 3 find user through email bc it is key done 4 compare passwords using bcrypt instance method in user model done 5 if user not found or password does not match the one in db throw unauthenticatederror done 6 if there is user password matches generate token using instance method done 7 send response with token done 9 think about expiresin set in env done 10 auth middleware 1 get user id done 2 pass it along to the jobs route done 3 test register user get token put the token in the header authorization will return userid name done 11 jobs model 1 make a schema for a jobs done 2 set type as an objectid so you may reference user as the creator of job done 12 create job route 1 we need to pass authorization header company position done 2 get the userid tie it as createdby so you cannot modify others work others cannot modify your work done 13 pass the token dynamically 1 set global variable in postman done login user tests const jsondata pm response json pm globals set accesstoken jsondata token now it is a global variable 2 use it in create job done authorization bearer accesstoken 3 use it in get all jobs as well done 4 test register user login user create a job get all jobs 14 create a job get a job update a job delete a job controllers all done 1 https mongoosejs com docs tutorials findoneandupdate html 15 test all job controllers done 16 work on mongoose errors will reuse in later projects done 1 validation errors done validatorerror please provide password at validate users ayazhan documents github job search website node modules mongoose lib schematype js 1270 13 at users ayazhan documents github job search website node modules mongoose lib schematype js 1253 7 at array foreach anonymous at schematype dovalidate users ayazhan documents github job search website node modules mongoose lib schematype js 1198 14 at users ayazhan documents github job search website node modules mongoose lib document js 2542 18 at process processticksandrejections node internal process task queues 77 11 properties validator function anonymous message please provide password type required path password value undefined kind required path password value undefined reason undefined symbol mongoose validatorerror true idea get error messages and separate them for more user friendliness 2 duplicate email done idea template string using values 3 cast error id syntax does not match exactly to what the mongoose is looking for done we don t get it in the auth but get it in the jobs earlier when we could not find job that matches the job id that was passed through the parameters we threw the notfounderror but it can also be the case that the syntax does not match whatever the database is looking for err stringvalue 64d83f72066651201e65f8634 valuetype string kind objectid value 64d83f72066651201e65f8634 path id reason name casterror message cast to objectid failed for value 64d83f72066651201e65f8634 type string at path id for model job 17 get the front connect with front 18 security protect api from attacks remark we cannot protect everything since the user can still store the token in a prone to attacks environment 1 helmet sets different http header to prevent numerous attacks used in many other packages as a dependency 2 cors ensures our api is accessible from a different domain make api accessible for the public 3 xss clean library sanitizes user input in req body req query req params protects from cross site scripting attacks where the attacker tries to inject some malicious code 4 express rate limit https www npmjs com package express rate limit minimizes the amount of requests a user can make deploy to heroku deploy via ui https medium com featurepreneur how to connect github to heroku be6ff27419d3 1 sign up 2 git 3 heroku cli https www google com search client safari rls en q heroku cli ie utf 8 oe utf 8 brew tap heroku brew brew install heroku heroku v 4 make mongodb access from all ports 5 duplicate project to desktop 6 delete any git repositories rm rf git 7 check if you have port ready for prod const port process env port 3000 8 check if app works app get req res res send jobs api 9 follow the steps here deploying node js apps on heroku https devcenter heroku com articles deploying nodejs 10 specify node version node v v18 16 1 11 change start script scripts start nodemon app js 12 make procfile https devcenter heroku com articles procfile to determine how to start your app heroku first looks for a procfile if no procfile exists for a node js app we attempt to start a default web process via the start script in your package json the command in a web process type must bind to the port number specified in the port environment variable if it doesn t the dyno doesn t start 13 deploying to heroku via git git init git add git commit m initial commit heroku login heroku create job applications website v1 git remote v check if git remote is pointing to the actual repo env variables 2 ways of setting up env vars heroku config set jwt lifetime value here via gui dashboard app settings reveal env vars add mongo uri and jwt secret git push heroku master restart all dynos add prod url as a global to postman https job applications website 1623c2b4d4e9 herokuapp com api v1 try login jobs routes 14 create swagger docs use postamn docs third part library to automate the process clone existing heroku app so you can keep the app on the cloud cd desktop heroku git clone a job applications website export postman collection 15 apimatic sign up for https www apimatic io import postman collection 16 edit api change name change url https job applications website v1 bd784586a4a7 herokuapp com api v1 save config change folders 1 auth login register 2 jobs export openapi v3 yaml 17 test in swagger editor https editor swagger io remove tags for misc jobs id in path name id type string 18 add swagger integration to app js const swaggerui require swagger ui express const yaml require yamljs const swaggerdoc yaml load job app swagger yaml app use api docs swaggerui serve swaggerui setup swaggerdoc changes 1 use mongoose validator instead of manual validation to get more meaningful messages previous way const name email password req body console log name email password if name email password throw new badrequesterror either name email or password is missing 2 do not store password in db directly hash data of any size bit string of fixed size use bcryptjs const register async req res check if any of name email password is missing const name email password req body console log name email password if name email password throw new badrequesterror either name email or password is missing pass as single arguments good for validation const name email password req body const salt await bcrypt gensalt 10 const hashedpassword await bcrypt hash password salt const tempuser name email password hashedpassword spread user attributes const newuser await user create tempuser res status statuscodes created json newuser even if someone breaks into the database they will not get the password but only hashed password which prevents them from easily reusing later never store passwords as strings more bytes random bytes const salt await bcrypt gensalt 10 more processing power knowledge base 1 what to send when we create a token depends on the needs of the front end however if you have created a token definitely send back the token because it will help the user access resources on the server later on 2 spread operator in the code snippet you provided the spread operator is used to pass the properties of the req body object as individual arguments to the create method the create method is likely a function or method that expects multiple arguments instead of a single object by using the spread operator the properties of req body are spread out as separate arguments to the create method here s an example to illustrate the usage of the spread operator javascript const userobject name john doe age 25 email johndoe example com without spread operator const user user create userobject with spread operator const user user create userobject in the first case userobject is passed as a single argument to the create method in the second case the spread operator is used to spread out the properties of userobject as separate arguments to the create method it s important to note that the usage of the spread operator depends on how the create method is defined and what arguments it expects if the create method expects a single object argument then the spread operator may not be necessary however if it expects individual arguments then the spread operator can be used to pass the properties of an object as separate arguments 3 instance methods for models https mongoosejs com docs guide html methods instances of models are documents documents have many of their own built in instance methods we may also define our own custom document instance methods userschema methods createjwt function const token jwt sign userid this id name this name process env jwt secret expiresin 30d userschema methods comparepassword async function givenpassword const ismatch bcrypt compare givenpassword this password true return ismatch how to use the method const token newuser createjwt 4 about jsonwebtoken expires in check out the docs here https www npmjs com package jsonwebtoken key generators allkeysgenerator com or https generate random org encryption key generator store it in env as jwt secret 5 authmiddleware i can only see my job others can only see their jobs const authmiddleware async req res next const authheader req headers authorization if authheader authheader startswith bearer throw new unauthenticatederror no token provided const token authheader split 1 try const decoded jwt verify token process env jwt secret attach the user to the job routes req user userid decoded userid name decoded name next catch err throw new unauthenticatederror authentication failed add to all jobs routes app use api v1 jobs authenticateuser jobsrouter 6 set type as an objectid to set type as an objectid so you may reference author as the author of book for example you may do like const book mongoose model book author type mongoose schema types objectid here you set the author id from the author colection so you can reference it required true title type string required true global variables 1 set global variables in postman 1 set global variable in postman login user tests const jsondata pm response json pm globals set accesstoken jsondata token now it is a global variable 2 use it in create job authorization bearer accesstoken 3 use it in get all jobs as well heroku for students authenticate via github next 1 deploy on netlify with frontend | server |
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generative-ai-falcon-40b-instruct-notebooks | large language model customization notebooks this repository provides a collection of generative ai engineering notebooks that demonstrate how to use amazon sagemaker jumpstart sdk to customize large language models llms the notebooks show using the falcon model variants how to apply basic levels of inference customization such as decoding strategies prompting techniques and retrieval augmented generation the notebooks are designed to be easy to deploy and follow making them a good resource for learning about llm inference customization the following amazon sagemaker studio notebooks are available in this repository llm custom decoding falcon40b g5 ipynb demonstrates how to generate text using different decoding strategies with amazon sagemaker jumpstart sdk https sagemaker readthedocs io en v2 82 0 overview html use prebuilt models with sagemaker jumpstart and falcon 40b instruct model https huggingface co tiiuae falcon 40b instruct llm custom prompting falcon40b ipynb demonstrates how to generate text using prompting engineering techniques with amazon sagemaker jumpstart sdk https sagemaker readthedocs io en v2 82 0 overview html use prebuilt models with sagemaker jumpstart and falcon 40b model https huggingface co tiiuae falcon 40b llm custom rag kendra falcon40b ipynb demonstrates how to use sagemaker https sagemaker readthedocs io en stable and boto3 https boto3 amazonaws com v1 documentation api latest index html sdks to generate text using the retrieval augmented generation rag pattern the notebook implements semantic search using amazon kendra https aws amazon com kendra enterprise search service the language model used for text generation is falcon 40b instruct https huggingface co tiiuae falcon 40b instruct to open a jupyter notebook using amazon sagemaker consider the two steps below 1 create or open an amazon sagemaker studio notebook https docs aws amazon com sagemaker latest dg notebooks create open html 2 clone this git repository in amazon sagemaker studio https docs aws amazon com sagemaker latest dg studio tasks git html security see contributing contributing md security issue notifications for more information license this library is licensed under the mit 0 license see the license file | amazon-sagemaker-notebook falcon-40b-instruct generative-ai large-language-models foundation-model-customization | ai |
MLP-Accelerator | mlp accelerator project homepage https wiki nus edu sg pages viewpage action pageid 167809322 labs repo https github com hsury nus ee4218 lab perceptron perceptron https github com hsury mlp accelerator raw main perceptron png system architecture system architecture https github com hsury mlp accelerator raw main system architecture png benchmark hardware platform zedboard xilinx zynq 7000 hdl 54us hls 65us c 69us | os |
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ArduRTOS | h1 align center ardurtos for arduino freertos public source repository h1 improve your freertos knowledge with high quality exams click here for atmel wikipedia https en wikipedia org wiki atmel click here for atmel avr wikipedia https en wikipedia org wiki atmel avr click here for arduino reference https www arduino cc reference en click here for the freertos kernel https www freertos org what it is what it is how to use how to use features features requirements requirements dependencies dependencies about about collaborators collaborators branches branches copyright licensing copyright licensing contributing contributing contact contact what it is ardurtos for arduino freertos library ardurtos guide is an easy and advanced way to learn freertos programming it will contribute greatly to both a hobby and a school lesson how to use just research the main repository https github com dentrax ardurtos and learn it gradually thats all warning before looking at the exams please try to solve it yourself first it s more important than anything it s a key to success features suitable for new freertos learners suitable cs101 content suitable for midterm and final exams more than 10 example content for every chapter rich content with screenshots and circuit diagrams soon requirements you should be familiar with c programming you will need a text editor i e sublime text or ide i e arduino ide you will need an arduino electronic programming platform if you want to test with usb cable skip this if you have an arduino virtual simulator or proteus you will need a computer on which you have the rights to install arduino dependencies dependencies arduino development libaries for building the freertos kernel for arduino arduino freertos h about ardurtos was created to serve three purposes ardurtos is a basically freertos programming learning repository coded in arduino c language using arduino ide 1 to act as a guide to learn basic arduino c programming with enhanced and rich content 2 to provide a simplest and easiest way to learn detailed and interesting things about freertos 3 there is a source for you to develop yourself in rtos and inreace your arduino programming level collaborators project manager furkan t rkal github dentrax https github com dentrax branches we publish source for the ardurtos in single rolling branch the master branch https github com dentrax ardurtos tree master is extensively tested and makes a great starting point for learning the rtos also tracks live changes https github com dentrax ardurtos commits master by commits copyright licensing the base project code is copyrighted by furkan dentrax t rkal and is covered by single licence all program code i e ino md is licensed under mit license unless otherwise specified please see the license md https github com dentrax ardurtos blob master license file for more information arduino https www arduino cc arduino is an open source computer hardware and software company project and user community that designs and manufactures single board microcontrollers and microcontroller kits for building digital devices and interactive objects that can sense and control objects in the physical and digital world atmel http www atmel com atmel is a leading manufacturer of microcontrollers and touch technology semiconductors for mobile automotive industrial smart energy lighting avr http www atmel com products microcontrollers avr default aspx avr is a family of microcontrollers developed by atmel beginning in 1996 these are modified harvard architecture 8 bit risc single chip microcontrollers freertos https www freertos org a00114 html freertos is an advanced realtimeoperatingsystem kernel references while this repository is being prepared it may have been quoted from some sources https www freertos org https aws amazon com freertos https github com feilipu arduino freertos library if there is an unspecified source or if you think that i made a copyright infringement please contact with me contributing please check the contributing md contributing md file for contribution instructions and naming guidelines contact ardurtos was created by furkan dentrax t rkal https www furkanturkal com you can contact by url contact https github com dentrax kbd best regards kbd | arduino freertos rtos arduino-uno arduino-mega arduino-platform arduino-boards examples example-project example-repo example-codes learning learning-exercise atmel | os |
Android_Mastermind-Game | mastermind this android app is based on mastermind board game https en wikipedia org wiki mastermind board game | front_end |
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BeerThermoregulationSystem | index index index beerthermoregulationsystem beerthermoregulationsystem subprojects components subprojectscomponents power specs and power supply requirements power specs and power supply requirements power supply minimum requirements power supply minimum requirements heat exchanger body heat exchanger body beerthermoregulationsystem div style float right margin 0 0 0 0 markdown 1 img src bts logo bts logo wrappedcircle whitebgd png alt logo width 200 div beer thermoregulation system based on peltier devices embeds mechanical design and electronic designs as submodules this project aims to provide a complete electo mechanical design whose role is to regulate fermenting beer temperature using water based heat exchanger subprojects components it comes with 3 main hardware components as opposed to 4 at the early days of the design main heat exchanger body with 3d cad design and 3d printed enclosures bts logicboard https github com bebenlebricolo bts logicboard blob main readme md electronic logic board whose role is to drive the power board with appropriate signals it is full featured and i designed it in a way that allows further improvements and extensions bts logicboard rev 0 3 0 https github com bebenlebricolo bts logicboard blob main documentation screenshots logicboard avr v0 3 0 png bts mainboard power https github com bebenlebricolo bts mainboard power blob main readme md this electronic board drives the 8 peltier modules used in this project and effectively acts as the main temperature regulation actuator it was designed to work at relatively high frequencies 1mhz in order to reduce the overall board size and components price bts mainboard power rev 0 2 0 https github com bebenlebricolo bts mainboard power blob main documentation screenshots bts mainboard power v0 2 0 front png power specs and power supply requirements each peltier module 12v 40x40 mm tec12706 manufacturer datasheet https docs rs online com aeb0 a700000007895121 pdf is able to draw 6 4amps and move 57w each which is the absolute maximum ratings for these devices in reality their efficiency is much lower which explains the numbers the power board itself was designed to handle 40 amps dc 12volts hence 480 w in order to feed those 8 peltier modules with around 5 amps each in both cooling and heating directions power supply minimum requirements for my tests i m using a beefy pc atx power supply 12v 40amps max with around 600w capabilities these board setup is running it to its very limits and i think that s not a good idea on the long run so the psu should be at least this powerful and able to deliver 40a steady dc current at 12v heat exchanger body heat exchanger documentation screenshots heatexchanger v0 1 0 all png heat exchanger internal cut documentation screenshots heatexchanger v0 1 0 internal cut y png | os |
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jmqtt | english readme cn md jmqtt jmqtt logo jmqtt png features full support of mqtt3 1 1 protocol support data persistence and clustering based on mysql support friendly secondary development plug in development cluster storage device connection publish subscribe authentication support tcp websocket ssl wss official documents official documents https arrogant95 github io jmqtt docs quick start 1 download release https github com cicizz jmqtt releases version above 3 x or clone this project 2 execute in the broker directory mvn ppackage all dskiptests clean install u 3 configuration file for configuration response jmqtt broker resources conf 4 execute the start command java jar jmqtt broker 3 0 0 jar h conf h is followed by the configuration file directory which needs to contain jmqtt properties and log4j2 xml online trial server address 81 69 46 38 tcp port 1883 websocket port 8883 ssl port 1884 wss port 8884 qq technology exchange group jmqtt jmqtt qq2 png test report jmqtt doc docs test report md | mqtt iot mq java | server |
LLMFuzzer | div align center llmfuzzer fuzzing framework for large language models llmfuzzer shell https github com mnns llmfuzzer assets 1796080 71b006df 706c 43f6 acd1 49646dbcb0e5 version https img shields io badge version 1 0 0 blue license https img shields io badge license mit green stars https img shields io github stars mnns llmfuzzer forks https img shields io github forks mnns llmfuzzer issues https img shields io github issues mnns llmfuzzer forthebadge https forthebadge com images badges built with love svg https forthebadge com forthebadge https forthebadge com images badges contains cat gifs svg https forthebadge com forthebadge https forthebadge com images badges not a bug a feature svg https forthebadge com div llmfuzzer is the first open source fuzzing framework specifically designed for large language models llms especially for their integrations in applications via llm apis who is this for if you re a security enthusiast a pentester or a cybersec researcher who loves to find and exploit vulnerabilities in ai systems llmfuzzer is the perfect tool for you it s built to make your testing process streamlined and efficient untitled https github com mnns llmfuzzer assets 1796080 a143897d 383c 4ed9 8b2f 65f4cdc5aa63 features robust fuzzing for llms llm api integration testing wide range of fuzzing strategies modular architecture for easy extendability roadmap adding more attacks html report as output multiple connectors json post raw post query get multiple comparers proxy support dual llm side llm observation autonomous attack mode get started 1 clone the repo bash git clone https github com mnns llmfuzzer git 2 navigate to the project directory bash cd llmfuzzer 3 install dependencies bash pip install r requirements txt 4 edit llmfuzzer cfg with your llm api endpoint llmfuzzer your application llm bash connection type http api url http localhost 3000 chat your llm api content json query attribute query your json query attribute output attribute answer your json response attribute headers enwiki session 17ab96bd8ffbe8ca58a78657a918558 add http headers if needed cookie enwiki session 17ab96bd8ffbe8ca58a78657a918558 add cookies if needed 5 run llmfuzzer bash python main py documentation we are working on full documentation it will cover detailed information about the architecture different fuzzing strategies examples and how to extend the tool contributing we welcome all contributors who are passionate about improving llmfuzzer see our contributing guidelines for ways to get started license llmfuzzer is licensed under the mit license see the license file for more details acknowledgments llmfuzzer couldn t exist without the community we appreciate all our contributors and supporters let s make ai safer together | ai cybersecurity llm llmsecurity | ai |
averylutz123.github.io | avery s eportfolio welcome to avery s eportfolio this eportfolio contains three enhanced computer programs that i originally developed during my four years in southern new hampshire university s computer science program these enhancements focus on exmeplifying my skills in software design and engineering data structures and algorithms and database management additionally this eportfolio contains an informal narrated code review and a professional self assesment that discusses my experience in snhu s computer science program and my artifact selections thank you for your time and i hope you enjoy my work table of contents 1 professional self assessment 2 informal code review 3 artifact one software design and engineering 4 artifact two data structures and algorithms 5 artifact three databases 1 professional self assessment since my acceptance into southern new hampshire university s computer science program in august of 2018 i have had the privilege of developing over fifty unique applications in five distinct coding languages although my experience at snhu has given me an opportunity to meet many students who were already well established in the field of computer science the only experience i had writing code prior to joining this program came from an introduction class i took at the former university i attended therefore every single class that i have taken over the past four years has shaped me into a programmer with efficient coding skills and a keen understanding on the importance of documentation throughout the completion of my snhu coursework and during the development of my computer science eportfolio i have gained numerous skills that will carry me forward into my future professional endeavors being able to make quick yet well calculated decisions think critically about the overarching functionality of my work and explain high level concepts to audiences of varying experience are just three of the skills that will significantly benefit my success in any career that i may choose to pursue with each assignment that i have submitted leading up to the final portfolio i have been able to effectively showcase my talents as a software developer in terms of the quality and complexity of the work that i deliver these talents are clearly demonstrated in my capabilities in software design and engineering in february of 2022 i was tasked with developing a c dice game named left center right for the final project of my it 312 software development with c net course this game was a simple text based game in which a random number generator was utilized to simulate a rolling die and then an action to correspond with each possible value result was displayed to the user throughout the entire it 312 course the completion of weekly labs that examined properly declaring data types implementing basic arithmetic and reading from text files acted as the foundation to the sills that would be required for the final dice game submission the completed dice game successfully incorporated three classes to distinguish different mechanics required for the game s functionality creative dialog to maintain the user s engagement and ten methods that organized the main program components this program was selected to represent artifact one within the portfolio due to the innovative techniques and creative nature that already existed within the game taking the opportunity to transfer the c text based game into a fully interactive mobile application showcased my skills in software design and engineering through the implementation of more robust code the utilization of industry standard practices and the incorporation of diverse gameplay mechanics i was able to take basic components of the original project and implement advanced techniques that scaled the simple text game to an application that is of professional standards for example the ability to read from a text file to display instructions transformed into the development of an instructions screen that exists as its own unique java activity that utilizes a scrollbar for easy navigation asking the user to input a y or n as an answer to whether or not they were ready for their turn was transformed into a button that allows users to simply roll whenever they choose even the utilization of diverse image placement that changes with each player s turn showcases an exemplary understanding of software design and engineering skills in collaborating in team environments were heavily showcased in my experiences within it 315 in this course microsoft visio was utilized to make highly detailed sequence diagrams method contracts and requirements traceability and verification matrices that were able to communicate the implementation of program features prior to the actual development of the code specifically it 315 focused on the development of a student information system program that was capable of registering a student into a specific course accessing their class records and determining the student s gpa in a collaborative environment it is essential for all participants to understand the foundation of the project before assigning roles and writing code therefore having multiple forms of documentation that discussed the prospects of the application in great detail demonstrated an excellent ability to communicate decision that will be made as well as their potential tradeoffs the planning techniques that were utilized for artifact three within the portfolio were greatly influenced by the diagrams and methodologies that were implemented in it 315 s student information system in artifact three s event tracker a collaborative environment is fostered through the detailed comments that accompany the program and the new features that were integrated into the code the event tracker which was originally developed in december of 2021 for cs 360 carried numerous design flaws that inhibited the program from fully functioning as intended additionally minimal comments were written within the program leaving many coding decisions unexplained and prominent features unsupported therefore it was important to review every existing piece of code and to document all functional components so that appropriate enhancements could be made artifact three s event tracker was predominantly selected for the eportfolio due to the considerable size of the database that stores all the information provided by the user the event tracker application provides users a platform to store information regarding future events they would like to remember the event tracker database houses three distinct tables provides crud functionality to the stored events and the permissions granted by the user with the enhancement of the program this database was upgraded to include a total of four new column tables two new program methods and extended functionality to segments of code that originally did not accomplish what they were intended to do additionally the database must be referenced throughout the entirety of the program including in the newly developed security questions and forgot password activities without the success of the database within the event tracker the entirety of the program would be unable to operate and the application could not exist as one of the most important concepts to grasp in computer science skills in data structures and algorithms were clearly demonstrated within the final project portfolio of cs 260 this program was selected to represent artifact two due to the roll that binary search trees vectors hash tables and linked list play in ensuring total functionality of the application each of these data structures exist within their own program in which they are utilized to manage the contents of bid information from an excel spreadsheet with the enhancements of the program each data structure can now perform all crud tasks upon the list of bids and can accept the user s input to personalize the searches that are made for specific items in order to successfully accomplish these enhancements data structure specific techniques needed to be utilized to ensure all values were being appropriately manipulated therefore this artifact is representative of my skills in utilizing data structures and algorithms 2 informal code review in this informal code review the three artifacts that were selected for enhancmet are examined and critiqued in terms of their current functionality organization and complexity the code for each artifact is analyzed in detail in order to ensure that areas for improvement are highlighted then the planned enhancement for each program is discussed this code review is approximately forty minutes in length please click the provided link to view avery s code review https www youtube com watch v 6njdgmt bmy 3 artifact one software design and engineering artifact one links to see the drastic improvements that have been made to the quality of the artifact one program it may be beneficial for some to compare the original version of the program and the final program enhancements the project has seen significant upgrades in terms of visual appeal interactive components and communications with the user therefore both the original code and enhanced program are linked below click to view the original c program prior to enhancment lcr original code https github com averylutz123 artifact one original click to view the enhanced artifact one program that represents skills in software design and engineering artifact one lcr enhancements https github com averylutz123 artifact one enhancement artifact description the artifact that has been selected to represent skills in software design and engineering was derived from the final project that was created within it 312 software development with c net titled final project 7 1 dice game originally developed in february of 2022 this program showcases a fully functional text based game named left center right lcr in which users take turns rolling the dice to see who can obtain and maintain the greatest number of gameplay chips in order for the program to achieve total functionality ten unique methods were utilized to distinguish the different gameplay mechanics such as rolling the dice and passing the chips additionally three classes were implemented to represent the program components that were associated with the player dice options and game features because the contents of the lcr game prior to the artifact s enhancements were confined to the text dialog within the console output the program ensured that any potential user input was accounted for so that the game could appropriately communicate no matter what the user entered while the lcr program was initially developed with the c programming language the enhancement for this artifact focused on transferring the code into a java mobile application this transfer to a different language has enabled the program to become a more interesting and interactive gaming experience that is more consistent with professional computer science standards colorful imagery interactive buttons multiple screens with diverse layouts and new dialog options were applied within the java mobile application to improve user engagement and to increase the desire for participants to replay the game multiple times therefore the transfer of the lcr program into a java mobile application resulted in the utilization of innovative skills and the implementation of design solutions that ensured a higher quality product was delivered upon completion artifact justification the lcr program was selected to represent artifact one within the capstone portfolio due to the potential that the original application possessed for becoming a genuine mobile game that could be uploaded to the app store and played by the general public the original version of the program merely existed as text dialog within the c console output in which the users and the game would communicate through a basic exchange of information however since the logic and instructions for the game are quite simple to understand the program was an ideal platform for showcasing exceptional enhancement skills during the reconstruction of the artifact into a comprehensive final product additionally the utilization of methods to separate different gameplay mechanics within the original lcr program provided a solid foundation for creating different screens that users could navigate through within the mobile application similarly it was clear that the utilization of widgets in the mobile application such as buttons would offer a more natural transition between the various gameplay mechanics as opposed to the pre existing functionality of accepting the user s input to progress forward therefore the lcr program provided an excellent opportunity for demonstrating skills in software design and engineering demonstrated skills and abilities within the artifact one enhancement the ability to use well founded and innovative techniques skills and tools in computing practices for the purpose of implementing computer solutions that deliver value and accomplish industry specific goals was effectively demonstrated the implementation of more robust and efficient controls can be seen in the removal of the three classes that existed within the original version of the program and the replacement of these classes with calls to the android specific intent class the three original classes were removed due to the minimal impact they had on the program s performance that resulted in needless repetition wasted space and redundant variable declarations calls to the intent class to pass data between each java activity within the mobile application not only provided easier readability of the code but also minimized the steps required for each gameplay mechanic to obtain total functionality another innovative feature that was implemented to minimize redundancy and to improve the efficiency of the program can be seen in the button widget that was incorporated into the calculaterollsactivity java file within this activity an if else statement is utilized to determine whether a user has enough chips a value greater than zero in the point tracker array to progress forward into the next activity then a single button is displayed to indicate that the user may roll the dice or skip turn by setting the text of the button to the designated response in the corresponding if else statement branch likewise each branch has a corresponding call to the intent class that will send the user back to the score board so that the next player may begin their turn or allow the current player to progress forward and roll the dice by utilizing this technique to advance the game forward the number of required java activities widgets and methods is minimized thus industry standard software designs were implemented into the program and the ability to utilize well founded and innovative techniques skills and tools in computing practices was further demonstrated the last significant indicator for exhibiting the ability to utilize well founded and innovative techniques skills and tools in computing practices for the purpose of implementing computer solutions that deliver value and accomplish industry specific goals can be seen in the effective organization of loops and branches that ensure smooth iterations between array elements these iterations show exceptional skills in array handling to test the user s input and to test the qualifications of each player until a winner is declared for example the program successfully iterates through the point tracking array to correctly determine when a single player element has a value equal to the total value of in game chips additionally the point tracking array and players names array needed to be passed between activities in order to correctly track the names of each player during every round and the number of chips distributed between all participants the culmination of these skills resulted in the development of a program that successfully demonstrates an exemplary understanding of software design and engineering enhancements 1 nine of the ten original methods that existed within the c version of the game were transferred to the java programing language these methods now exist in the form of new methods that spread throughout the entirety of the program or as individual java activities the politequestion method was not included within the enhancements of the artifact since users were no longer required to enter text dialog to progress forward and thus unexpected responses did not need to be accounted for 2 ten new java activities were created to represent the different screens users will navigate through 3 ten new xml files were created to provide a clean and organized layout for each screen the users will interact with 4 fourteen new drawable png files were imported into the program to be utilized as imagery 5 the strings xml file was updated to include forty new string values that are called throughout the program 6 a new functional component was created to read from an external text file to display text discussing the creation and purpose of the game titled about 7 a new method was developed that displays three different images each time a player rolls and the method is called an if else statement is utilized to select from six drawable options or the default image is utilized 8 scroll bars were implemented in five xml layout files so users can move up and down the screen when required to continue reading text that is not visible upon the activity start 9 ten buttons were implemented as a mechanism for users to progress further into the game 10 a new feature was added that instructs players on the order in which they should be sitting so that the chip passes are accurate to their real life seating arrangement 11 removed program content such as the three unnecessary classes that resulted in redundancy repetition and inefficient 12 improved comments within the code to correctly describe the purpose of major segments 13 ensured formatting throughout each activity and xml file was well structured consistent in style and consistently formatted 14 ensured code was error free objectives throughout the enhancement of artifact one all corresponding objectives that had been planned prior to development were fully met and the expectations of these objectives have been exceeded within artifact one innovative skills and techniques for implementing design solutions and accomplishing goals are demonstrated in the logical breakdown of each activity into clear segments of functionality none of the individual program activities or methods are needlessly complex or contain content that extends past their intended purposes for example the calculaterollsactivity java file strictly exists to determine the number of rolls allotted to each player and to display the computed value onto the screen for users to read determining which activities or screens should be incorporated into the project also required creative decision making as the original version of the program had no such need for this level of organization since the contents of the program were only displayed in the console output reflection throughout the process of enhancing the lcr artifact i learned the importance of focusing on big picture concepts instead of only fixating on little details while the entirety of the final program is in fact comprised of little details that each needed to obtain total functionality trying to perfect a single feature before the majority of the project exists can take time away from forming a cohesive and uniform product therefore i learned that breaking down the broad goals of the project into various tasks based on functionality allowed me to build the program up in layers for example when creating a new activity the first thing that needed to be accomplished was laying out the basic framework for the necessary widgets within the xml file without thinking about details such as fonts placement or color then each widget was linked to the necessary functional components within the java file in which new methods would be added in order of importance then the last step is to make the entire activity look visually appealing on the screen by adjusting colors and importing pictures in this enhancement i learned that the little details of the project are absolutely important however they provide few benefits when other sections of the program are inadvertently being overlooked the biggest challenge that i faced while developing this artifact was relearning how to work within android studio my experience with the ide is quite minimal since i had only ever created a handful of small mobile application during my time in cs 360 in december of 2021 in fact i had not worked with java in a meaningful way since that course had ended so the initial days of working on the lcr program revolved around learning basic concepts such as placing widgets linking xml and java file contents and applying functionality to widgets within each activity even objectives that i typically excel in accomplishing such as reading from external text files seemed more complicated in the mobile application format since the contents of the xml file always had to be considered with every decision however despite this challenge the completed application turned out to be an enjoyable and well designed product the feedback for this artifact with its original submission was to improve the manner in which i discuss the course outcomes within the narrative specifically i originally mentioned that i met all objectives but i needed to identify and articulate which outcomes i met within the enhancement therefore i changed the formatting of my narrative to specifically discuss how the artifact was improved in terms of the main skill that was exhibited using well founded and innovative techniques skills and tools in computing practices for the purpose of implementing computer solutions that deliver value and accomplish industry specific goals i created a clear header for this section of my narrative titled demonstrated skills and abilities and stated the skill at the beginning of the first paragraph i also incorporated some of the indicators of success to ensure my accomplishments were more obvious 4 artifact two data structures and algorithms artifact two links throughout the enhancement of artifact two significant improvements were made in program functionality code readability and user engagement therefore it may be beneficial to review the original contents of artifact two in order to truly vizualize the strides that were made in strengthening the program s overall quality and efficiency both links to the original version of artifact two as well as the enhancement are linked below click to view the original data structure portfolio prior to enhancment data structure original https github com averylutz123 artifact two original click to view the enhanced artifact two program that represents skills in data structures and algorithms artifact two data structure enhancements https github com averylutz123 artifact two enhancement artifact description the program that was selected to represent artifact two within the series of enhancements that were completed for this portfolio was the 7 1 final project portfolio from cs 260 data structures and algorithms originally developed in february of 2020 this c portfolio features four separate programs that highlight the main differences and benefits of some of the most commonly utilized data structures binary search trees hash tables linked lists and vectors are each implemented in their own distinct programs where they allow users to navigate through two microsoft excel files that contain information pertaining to the bidding statistics of items that were submitted during an auction of property these programs allowed users to select from a menu of options in which they could originally display the bids search for a specific bid or remove bids after the contents of the excel file had been read additionally the vector sorting program allowed users to complete a quick sort or selection sort in order to place the list of auction items in alphabetical order although the goals of the four portfolio programs were similar in terms of their intended purposes due to the differences in the implemented data structures and algorithms each program utilized unique techniques to obtain total functionality artifact justification the 7 1 final project portfolio from cs 260 was selected to represent artifact two with the enhancement strategy focused on algorithms and data structures due to the exceptional utilization of data management practices within each of the four programs because the project itself was designed with the intention of demonstrating the advantages of various data structures and algorithms it was an ideal candidate for exhibiting skills in implementing algorithmic principles computer science practices and computing standards to solve existing problems within the code additionally the state of the programs prior to enhancement left ample room for improvements since the original functional goals of the project were fundamentally related to the computer programming crud operations create read update delete however since the programs were only designed to read and delete bids within the list of items the logical improvement that could be made to the code was to include the ability to add and update user specified bids as well demonstrated skills and abilities within the artifact two enhancements the skill of designing and evaluating computing solutions that solve a given problem using algorithmic principles and computer science practices and standards appropriate to its solution while managing the trade offs involved in design choices was demonstrated this skill was exemplified in the development of the new update and create methods that were incorporated into each program to solve the project s previous shortcomings in obtaining total crud functionality with the inclusion of these methods each program can now successfully create read update and delete information within the specific data structure that exists in each program since the approach utilized to navigate through each of the four data structures vastly differ from one another it was essential for structure specific techniques to be implemented within each program for example the hash table program required the implementation of a node pointer bid key and while loop to update the contents of an existing bid whereas the vector sorting program only required the vector element value for the bid in question therefore determining the appropriate strategy for each program required an in depth knowledge and an excellent ability in evaluating computing solutions for logic problems the skill of designing and evaluating computing solutions that solve a given problem using algorithmic principles and computer science practices and standards appropriate to its solution was also demonstrated in the advancements made to the user menu prior to enhancement the menu controlled switch statement s lack of communication with users alongside the code s inability to steer users into selecting appropriate menu options often times resulted in inaccurate selections or complete failure in functionality now a default option exists so that unacceptable inputs are appropriately handled and the user is directed to try again similarly logic problems that existed within the original search and remove methods have been resolved by providing users the ability to input their own unique bid ids originally the program only allowed the default key to be searched for and removed thus the entire application only existed to manage one bid out of the minimum of 179 that exist in the excel file by highlighting logical problems seen within the user menu and implementing appropriate measures to improve interactivity and cooperation between those utilizing the program and the fictitious municipal government data feed that obtained the list of bids the program is able to accomplish a greater variety of tasks in a more efficient manner within the artifact two enhancements the skill of developing a security mindset that anticipates adversarial exploits in software architecture and designs to expose potential vulnerabilities mitigate design flaws and ensure privacy and enhanced security of data and resources was clearly demonstrated this skill is highlighted in the improvements made to every case within each program s main menu switch statement and the value checks that were implemented in several methods beyond the new default option that was incorporated into the switch statement to support the functionality of the menu multiple if statements were implemented to act as safeguards in assuring that bids are loaded prior to being manipulated now if a user selects an option other than load bids as their first course of action upon loading the program the user is informed that they must load the bids before progressing forward another example of a security mindset being demonstrated throughout the enhancement of artifact two can be seen in the incorporated value checks that ensure bids exist prior to the completion of any crud activities now users of the program can access complete and correct data without causing errors to occur since numerous if statements have been incorporated to examine whether or not a requested bid id exists within the program s specific data structure if the bid id does not exist the expected crud activity does not occur and the user is informed that the action could not be completed thus all data is validated to ensure the program can run until the user decides to exit the application likewise ten warnings existed within the program prior to enhancement that expressed potential vulnerabilities within the application that could be exploited for example five comparison between signed and unsigned expressions warnings were given in the vector sorting program at different for loops with these warnings and without proper variable declarations many for loops had the potential to return incorrect and unaccepted values in resolving these issues a coding environment with clear communications and efficient navigation without easily exploitable vulnerabilities was cultivated enhancements 1 included two new cases within the menu switch statement in the binarysearchtree cpp hashtable cpp linkedlist cpp and vectorsorting cpp programs these new cases center on the creation of new bids and the ability to update existing bids 2 included an additional case in the vectorsorting cpp program to delete existing bids 3 added a default case within the menu switch statement in all four programs now unexpected user inputs are accounted for 4 included an if else statement within five of the cases of each program s menu switch statement to ensure all bids have been loaded prior to completing any further actions these if else statements act as a safeguard to ensure the crud tasks can be completed and to prevent the program from experiencing debilitating errors 5 incorporated an update method within each program these methods successfully examine the contents of each program s corresponding data structure locates the bid in question and accepts the user s input to change specific data members within the structure 6 implemented safeguard measures within each update delete and search method to ensure unexpected user inputs are accounted for and to direct users back to the main menu when necessary 7 incorporated a createbid method within the binarysearchtree cpp and hashtable cpp programs this method accepts three user inputs and formats their inputs into appropriate data members the method then appends the newly created bid to the end of the existing list of bids 8 implemented a means for user specified bids to be searched for and removed from each program s particular data structure originally the program s depended on a single default bid and did not accept the user s input 9 reformatted and added new comments to create a more professional program that clearly communicats the contents of each method switch statement case and data structure modifications 10 created a delete method within the vectorsorting cpp program that accepts an input from the user and then erases the designated bid from the existing list in the bids vector 11 removed all program warnings that resulted in logic problems that had the potential to cause errors to occur 12 utilized data structure specific techniques to handle data appropriately in each program and ensured coding best practices were being followed objectives throughout the enhancement of artifact two all corresponding objectives that had been planned prior to development were fully met and the expectations of these objectives have been exceeded within the enhancements of artifact two a security mindset that anticipates adversarial exploits in software was exhibited and computing solutions that solve a given problem using algorithmic principles and computer science practices and standards appropriate to its solution were implemented the entirety of each program was reformatted so that the code is complete and correct in design the code is well structured consistent in style and consistently formatted and each method is written to be as efficient as possible the enhancement of this artifact transformed a simple program with minimal functionality into an application that allows for professional quality user engagement and an extensive list of features reflection while working on the enhancements to artifact two it was important to consider how the new additions to the project would impact the functionality of existing methods since each program had well over three hundred lines of code any changes to the main method of each program had the potential to significantly influence method calls variable assignments or points of termination in any existing loops therefore frequently testing the output of the original features in the program in addition to the new enhancements within the code became an essential factor in delivering a correct complete and error free artifact through this testing i learned how to properly utilize the debug feature within eclipse since none of the projects i have previously completed within the ide required its assistance i have not worked in eclipse in almost two years as many of my c programs are created in visual studio so overcoming the differences in their window formatting perspective and the debugging feature was quite a challenge while both ides exist for the purpose of aiding programmers in developing their code understanding the little variations between both environments really benefited the quality of the delivered artifact completing the enhancements to this artifact also gave me a better understanding on how to correctly implement pointers since they are something i typically try to avoid them in my work while i am educated on the benefits of pointers and how they are utilized within a program i have always found them to be a bit convoluted since i usually focus on a program s functionality in terms of the literal code being written and not the memory spaces in which the variables data members and vector elements are being stored in general pointers seemed like such an abstract concept to me because they require an understanding of the program beyond what could be seen in the console output therefore learning how to correctly utilize pointers was the greatest challenge i faced while working on artifact two s enhancements because their incorporation played such a vital role in navigating throughout many of the data structures having existing program methods that also utilized pointers was incredibly beneficial in learning their correct implementation as i got to make changes to these existing features and see how it impacted the output of the program in future programs i will be less hesitant in utilizing pointers as they provided such a massive benefit in the efficiency in the artifact two enhancements after submitting the first version of artifact two s enhancements i received feedback regarding the quality of my narrative specifically i was asked to remove any i believe and i think statements with the completion of the final enhancements my narrative has been improved so that the skills and abilities exhibited throughout my work are discussed in a manner that is confident and unopinionated additionally since the original submission i made the decision to increase the functionality of the vectorsorting cpp program to include a delete bid feature this enhancement was not included with in my original plans however it seemed necessary to include so that all four programs are cohesive in expectations and style additionally the incorporation of a delete feature in the vectorsorting cpp program ensured all crud functionalities existed across all four programs without any exceptions 5 artifact three databases artifact three links throughout the enhancement of artifact three substantial changes were made in the features that the event tracker application was able to accomplish the new additions to the program provide a more proffesional appearance that makes the final product more in line with industry standards with these changes the mobile application could be uploaded to the app store for the general public to experience both the original and enhanced programs are linked below click to view the original event tracker prior to enhancment event tracker original https github com averylutz123 artifact three original click to view the enhanced artifact three program that represents skills in database management artifact three databases https github com averylutz123 artifact three enhancement artifact description in order to demonstrate expertise in the computer science skill of database management the 7 1 final project event tracker from cs 360 mobile architecture and programming was selected as the category s artifact for enhancement developed in december of 2021 this java mobile application was designed to offer users a platform to store information related to future events they will be attending and notifying the users via text message when a new event was entered into the program s database the original functional components of the program included a login screen that ensured users were only accessing events that corresponded to their unique username and password the ability to edit and delete event information after the event had been saved into the database and the ability to send an sms notification if the users granted the program permission to accomplish the task the success of these functional components heavily relied on the program s sqlite database which was comprised of three distinct tables that represented the user accounts the list of events that corresponded to specific user accounts and information associated with each individual event through the implementation of the sqlite database the program was able to effectively allow multiple users to store the details of events in a uniform location without scrambling the contents of each account artifact justification the cs 360 event tracker mobile application was selected as the artifact to represent the category of database enhancements due to the significant role that the sqlite database plays in ensuring complete and correct functionality of the program because storing user and event information was foundational to accomplishing the functional goals that were initially set out for the program the application would not be able to exist without the proper implementation of the database therefore as an incorporation into a portfolio that is intended to showcase vital areas of expertise as a computer science professional the event tracker was undoubtedly the most fitting example of admirable database management capabilities furthermore the original version of the application had broad expectations that left ample room for the integration of innovative and more advanced features when selecting this artifact to be included within the eportfolio it was apparent that the addition of several new features would bring the entirety of the event tracker mobile application to a greater professional standard demonstrated skills and abilities within the artifact three enhancements the ability to employ strategies for building collaborative environments that enable diverse audiences to support organizational decision making in the field of computer science was demonstrated within the enhancement of the event tracker artifact existing in code comments were improved upon in order to provide easily readable and understandable code to those who may examine the program the original comments left within the program were ill formatted and did not contain enough details for diverse audiences to understand the contents of the code additionally in some portions of the program entire methods and java activities were left uncommented thus no context was provided for the features that were being incorporated into the application due to the large scale of the program the lack of comments made it difficult to understand the software design choices that allowed the program to obtain total functionality to alleviate this issue comment headers were included at the top of each java class to summarize the functional components that are presented within the code and to explain how these components are perceived by the users the employment of strategies for building collaborative environments that enable diverse audiences to support organizational decision making in the field of computer science can also be seen in the implementation of the newly created permissions and security questions activities now when creating an account users are instructed to answer three security questions that can be recalled at a later date to access their account if their password is forgotten each question is represented within the database as three columns within the user account table and are recalled in the corresponding java class as three new variables the addition of this feature allows users to interact with the program with more confidence as human errors are now accounted for and each account is protected with a heightened level of security therefore a collaborative environment between the users and the program is fostered since the enhancements made to the program s database support the storage of clean and usable data that can be easily retrieved and presented in a timely fashion within the artifact three enhancement the ability to design develop and deliver professional quality oral written and visual communications that are coherent technically sound and appropriately adapted to specific audiences and contexts was showcased this skill is demonstrated through the incorporation of a notification switch that allows users to determine whether they would like to receive notifications on an individual event basis while the majority of the event tracker application exists in the form of text dialog in order to convey pertinent information back to the user the implementation of a switch provided an opportunity to diversify the layout of the event information activity and to highlight a predominant feature that the application offers additionally the result of the user s decision on whether they would like to be notified is then converted to text once all event information has been entered in order to communicate information in a clearer and more stylistically uniform manner thus both visual and written communications were considered with the implementation the notification switch enhancements 1 included a new java activity titled securityquestions java that allows users to answer three security questions so that their password can be retrieved at a later date if it is forgotten 2 included a new java activity titled forgotpassword java that allows users to re answer the previously saved security questions so that their password can be revealed if it was forgotten 3 included three new columns within the user account table in the program s database in order to store the results of the new security questions 4 created a new method within the program database that insert s the answers to the three security questions into the appropriate corresponding user account within the table 5 created a new method within the program database that allows for a single event to be retrieved based upon the name of the event provided 6 implemented appropriate mechanics so that the previously created deleteevents method can function as intended 7 included a new column within the event information table in order to represent the new notification feature 8 implemented a switch widget within the information edit activity so users can decide whether they want to receive notifications on an individual event basis 9 modified eleven database methods to include the new program columns that were incorporated into the event information table and user account table 10 created two new xml layout files to represent the forgot password and security questions screen 11 improved the wording and functionality of the dialog boxes that are displayed within the permissions activity 12 added comment headers to each java class to better explain the purpose of each individual activity as well as the user s perspective of the activity s functionality 13 ensured that the code was well structured consistent in style and consistently formatted objectives throughout the enhancement of artifact three strategies for building collaborative environments were employed and a professional application that clearly communicates its capabilities to diverse audiences was delivered upon the completion of the planned enhancements for the event tracker this objective was met and expectations surrounding this objective were exceeded in accordance with standards seen in professional mobile application development a program that allows for multiple users to save their personalized content should provide users a means to access their account if their password was forgotten the utilization of security questions is a common computing practice that ensures the user s privacy is kept while also easily verifying the identity of the user thus innovative techniques such as requiring the three answers to the security question as well as a username to be the parameters of the method getuserpassword ensured there was a perfect match for all four variables before revealing the corresponding password to the user with the implementation of this feature within the program industry specific goals were accomplished and a strengthening of program security was created reflection while enhancing the cs 360 event tracker mobile application i learned how to independently manipulate characteristics of the program s database without the utilization of external resources the original creation of this application was one of the most difficult final projects i had worked on during my computer science program at snhu and i did not fully understand the reasoning behind many of the lines of code that were used within the database when taking cs 360 i needed to spend numerous hours analyzing textbook examples just so i could meet the expectations within the rubric however while the code i implemented was generally correct i more or less was following patterns that existed within previous classroom examples and putting together different lines of code like a puzzle until i received the output i wanted before diving into the enhancements for this project i spent time going through every program file and reading the contents of each method to understand what every line of code was intended to accomplish i also utilized breakpoints while running the program so i could clearly understand what was being accomplished by taking time to learn how and why the program was able to correctly operate including my planned enhancements became an easier task when developing the new features that were to be included within the enhancement of the event tracker application the greatest challenge i faced was implementing the ability to delete events the reason as to why this task was difficult is because of my original decision to separate the tables of event and event information the contents of the event table simply include the event s name update time and the username that the event was created under however the event information table includes the actual logistics of the event that the user must answer such as the event s date time and additional notes this decision made deleting the event in its entirety the related content in both the event and event information tables rather difficult this situation was made worse by the fact that the java activity that allowed for the user to delete or edit event information did not need to obtain data from the event table and thus it had not yet been declared eventually my solution to these difficulties was creating tables in the database getevent and deleteevent to retrieve a matching event from the existing list in the user s possession and then passing that retrieved event to be removed from the database since i initially submitted artifact three faults that existed within the original segments of the code became more apparent and more destructive to the functionality of the enhancements therefore a significant amount of time was spent improving portions of code that were written when the program was first developed for example the permissions activity unintentionally carried the permission status across multiple user accounts since it made changes to the application s status within the phone thus when more than one user consecutively tried to grant the program permission to send sms text messages the application would eventually come to a halt due to a fatal error because this error acted as a roadblock in providing functionality to the security questions it was essential for the problem to be resolved | server |
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Azure-AW | div align center a href https lookerstudio google com reporting da5da0af 4be0 4f7d a84b f7c2892df612 img src https github com hamagistral azure aw assets 66017329 9f2c3cb9 932a 476d 8f3f 9952e1ea111d alt banner width 720 a div id user content toc ul summary h1 style display inline block analyzing sales of adventureworks h1 summary ul div p on prem db to azure cloud pipeline with data factory lake storage spark databricks synapse powerbi p div br table of contents 1 project overview introduction 2 key insights key insights 3 project architecture project architecture 3 1 data ingestion data ingestion 3 2 data transformation data transformation 3 3 data loading data loading 3 4 data reporting data reporting 4 credits credits 5 contact contact a name introduction a project overview this an end to end data engineering project on the azure cloud where i did data ingestion from a on premise sql server to azure data lake using data factory to transformation using databricks and spark loading to synapse and reporting using powerbi also i used azure active directory aad and azure key vault for the data monitoring and governance purpose dataset adventureworks is a database provided by microsoft for free on online platforms it is a product sample database originally published by microsoft to demonstrate the supposed design of a sql server database using sql server 2008 here are some key points to know about adventureworks adventureworks database supports a manufacturing mnc named adventure works cycles it is a sample online transaction processing or oltp database which is a type of data processing where multiple transactions occur concurrently these are shipped by microsoft with all of their sql server products for this project i used the lightweight lt data a lightweight and pared down version of the oltp sample download here https github com microsoft sql server samples releases download adventureworks adventureworkslt2022 bak project goals establish a connection between on premise sql server and azure cloud ingest tables into the azure data lake apply data cleaning and transformation using azure databricks utilize azure synapse analytics for loading clean data create interactive data visualizations and reports with microsoft power bi implement azure active directory aad and azure key vault for monitoring and governance a name key insights a key insights total revenue by product category touring bikes is the top 1 category generating revenue with 32 followed by road bikes with 26 and mountain bikes with 24 sales by country n 1 the united kingdom uk have the most total sales with 278 and 572 000 of total revenue n 2 the united states of america usa is second with total sales with 264 and 383 810 of total revenue revenue by gender 81 of the revenue is generated by male customers 19 of the revenue is generated by female customers this can be explained by males have more interest in doing outdoor activites with the different categories of bikes than females a name project architecture a project architecture you can find the detailed information on the diagram below azurepipeline hamagistral https github com hamagistral azure aw assets 66017329 ebb0f88b 917f 4a6a be6b ddf6093ad793 a name data ingestion a data ingestion connect the on premise sql server with azure using microsoft integration runtime image https github com hamagistral azure aw assets 66017329 b57debac 28c2 4928 8640 676643e0177c setup the resource group with needed services ressource group https github com hamagistral azure aw assets 66017329 62990af9 db6e 4712 81bf 61420835bb99 migrate tables from on premise sql server to azure data lake storage gen2 image https github com hamagistral azure aw assets 66017329 2b9855a9 9ad7 4ac3 8076 70762ef0f3bc df pipeline https github com hamagistral azure aw assets 66017329 21ed74aa 8bf4 46c5 952c 4dc9f14dc9fb a name data transformation a data transformation mounted azure blob storage to databricks to retrieve raw data from the data lake used spark cluster in azure databricks to clean and refine the raw data achieve the cleanest form of data delta format optimized for further analysis image https github com hamagistral azure aw assets 66017329 11b7fb4e 0013 4a9f a791 ab2a2789f774 a name data loading a data loading utilize azure synapse analytics to load the refined data efficiently create sql databases and connect them to the data lake synapse pipeline https github com hamagistral azure aw assets 66017329 99a8c7cd 1a6f 4ec9 b35d 2e171d3be87b db synapse https github com hamagistral azure aw assets 66017329 b601eb00 efe1 44d9 8de6 8f001176d549 a name data reporting a data reporting connected microsoft power bi to azure synapse to create interactive and insightful data visualizations powerbi dashboard https github com hamagistral azure aw assets 66017329 30bb3c61 1503 42a3 8b03 cd7c3da7bb82 technologies used data source sql server orchestration azure data factory ingestion azure data lake gen2 storage azure synapse analytics authentication and secrets management azure active directory and azure key vault data visualization powerbi a name credits a credits this project is inspired by the video of the youtube channel mr k talks tech https www youtube com watch v iq41wqhhglk a name contact a contact me linkedin https www linkedin com in hamza elbelghiti website https hamagistral me gmail hamza lbelghiti gmail com | cloud |
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computer-vision-interview | computer vision interview interview questions to ponder related to computer vision imaging systems rough overview of a camera calibration process say you have acquired a number of constraints for example during camera calibration process how do you solve the system of the constraints e g describe gradient method in 3 4 sentences describe the sources of noise in an image sensor how does a camera see in color draw the schematic of a 3t pixel architecture list out all of the lens parameters you can think of you ve got a camera that powers on and takes pictures but the images it captures are very dim what could be the potential problems what are the typical voltage levels required to operate an image sensor what power domains do these voltages supply to your image is blurry what are the potential issues explain fixed pattern noise fpn where does it come from how do you correct for fpn how do you configure an image sensor how does data get out of an image sensor what are some standards you know of suppose you have a flash led that can deliver a high lumen output for a fraction of a second but no more how would you synchronize the led with the start of a frame mathematics what are eigenvalues and eigenvectors implement sqrt const double x without using any special functions just fundamental arithmetic 3d image processing what is the camera matrix and what does it consist of how to convert the point for 3d world coordinates into 2d image coordinates how to eliminate corners in a bunch of 3d point cloud how to find shape object correspondences in 3d point cloud assuming you have an image and depth points for every pixel around an object how would you create a 3d model of that object given n correspondences between n images taken from cameras with approximately known poses find the position of the corresponding 3d feature point given a set of coordinates of joints perform a rotation such that the hips are perpendicular to the camera 2d image processing rough overview of optical flow estimation again just 3 4 sentences what are the necessary assumptions during optical flow estimation answer constant image brightness no lens shutter distortion how would you code up a custom rectangle detector how would you send an encoded message in an image first encode it then write code to decode it write a function to produce the convolution of an image with a filter implement canny edge detection using graphs how would you implement a connected components labeling in a binary image how would you remove outliers when trying to estimate a flat plane from noisy samples content based image retrieval cbir also known as query by image content qbic is implemented how describe how convolution works what about if your inputs are grayscale vs rgb imagery what determines the shape of the next layer how do you rotate an image 90 degrees most efficiently if you don t know anything about the cache of the system you re working on implement voronoi clustering given a mxn matrix where each element can either be 0 or 1 we need to find the shortest path between a given source cell to a destination cell connected components make a histogram of 2 variables color science stuff about colorspace transformations and color based segmentation esp talking about yuv lab hsv etc what is metamerism why do we have different color spaces what is the color space your eyes see in detection and tracking how does image registration work sparse vs dense optical flow and so on you re in deep space with a star atlas and a calibrated camera find your orientation how do you implement loop closure detection in slam linear algebra x belongs to a s null space then what does that mean how to calculate covariance given a set of data transpose a matrix first do it using extra memory then do it in place implement a sparse matrix class in c implement a dot product method on the class create a function to compute an integral image and create another function to get area sums from the integral image detection features what visual features do i know sift surf orb etc how does the detector of the feature x work what is a difference between sift and surf how can you detect car through cctv camera write a function that fills a buffer with a rolling set of image object segmentation results implement non maximal suppression as efficiently as you can metrics why does one use mse as a measure of quality what is the scientific mathematical reason for the same string manipulation write the c function for the atoi function machine learning describe the functionality and usage of lrn normalization layer in alexnet what is a neural network from a set of loss functions like l2 loss or hinge loss explain which ones are rotationally invariant sensitive to rescalings of the input features and which are convex given a set of standard random forest trees and a set of gradient boosted trees explain how the model s predictions would change if you remove the first tree the last tree or make other changes after training describe back propagation how can you tell if you ve underfit or overfit what are sigmoid and relu activations how do vanishing and exploding gradients factor into both of these activations given stride and kernel sizes for each layer of a 1 dimensional cnn create a function to compute the receptive field of a particular node in the network this is just finding how many input nodes actually connect through to a neuron in a cnn clustering write code for k nearest neighbor algorithm operating systems what is meant by virtual memory data structures write a function to delete a duplicate node within a linked list time complexity of insertion in linked list vs array write a function to create a list for every level within a binary tree how can you find 2nd highest number in an array in least time add a node to a linked list design patterns what is a singleton how and when is it used software engineering what is the difference between debug and release mode what is the purpose of revision version control design a web service that provides computer vision computations on input images how would you test it how would you deploy it what is a monkey patch given an algorithm describe your process to turn it into production worthy code pandas given a pandas dataframe with some numeric columns how to produce counts of data for different category ids including with or without extra processing to remove noisy missing or outlier data points object oriented programming what is inheritance polymorphism algorithms check whether two words are anagram with each other reverse a bit string reverse a linked list in place there is a building with 100 floors you are given 2 identical eggs how do you use 2 eggs to find the threshold floor where the egg will definitely break from any floor above floor n including floor n itself how do you get the count of each letter in a sentence given a list a of objects and another list b which is identical to a except that one element is removed find the removed element given a list of integers positive negative write an algorithm to find whether there s at least a pair of integers that sum up to zero how would you improve your algorithm s performance write a function which handles the placement of tetris blocks in a tetris game statistics you randomly draw a coin from 100 coins 1 unfair coin head head 99 fair coins head tail and roll it 10 times if the result is 10 heads what is the probability that the coin is unfair you re about to get on a plane to seattle you want to know if you should bring an umbrella you call 3 random friends of yours who live there and ask each independently if it s raining each of your friends has a 2 3 chance of telling you the truth and a 1 3 chance of messing with you by lying all 3 friends tell you that yes it is raining what is the probability that it s actually raining in seattle consider a game with 2 players a and b player a has 8 stones player b has 6 game proceeds as follows first a rolls a fair 6 sided die and the number on the die determines how many stones a takes over from b next b rolls the same die and the exact same thing happens in reverse this concludes the round whoever has more stones at the end of the round wins and the game is over if players end up with equal of stones at the end of the round it is a tie and another round ensues what is the probability that b wins in 1 2 n rounds you re at a casino with two dice if you roll a 5 you win and get paid 10 what is your expected payout if you play until you win however long that takes then stop what is your expected payout cuda implement viola jones in cuda general programming how do you average two integers without overflow multithreaded programming how do you create concurrent programs that operate on the same data without the use of locks frameworks language specific know how to use open neural network exchange format onnx use a python built in package to manipulate csv data databases given a kpi choose the right metric perform etl using sql code | ai |
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2021v-public | web application development spring 2021 semester common repository for the web application development course at isel https www isel pt spring 2021 semester see moodle https 2021moodle isel pt course view php id 5901 for additional information on this course | front_end |
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tdesign | p a href https tdesign tencent com target blank img alt tdesign logo width 200 src https tdesign gtimg com site tdesign png a p english readme zh cn md tdesign is a comprehensive enterprise design system https tdesign tencent com design values and component libraries have been implemented for versions such as vue https tdesign tencent com vue react https tdesign tencent com react and wechat miniprogram https tdesign tencent com miniprogram tdesign has advantages when used for building applications with consistent design consistency and cross platform multi tech stack comprehensive capabilities tdesign https user images githubusercontent com 88708072 147124305 fbb74f9f 65b2 44f9 9f1c e812ce63a547 gif repositories the following are the repositories for tdesign repositories for desktop components repository description status tdesign vue https github com tencent tdesign vue vue js ui components lib for tdesign 1 0 lts tdesign vue next https github com tencent tdesign vue next vue3 x ui components lib for tdesign 1 0 lts tdesign react https github com tencent tdesign react react ui components lib for tdesign 1 0 lts repositories for mobile components repository description status tdesign miniprogram https github com tencent tdesign miniprogram wechat miniprogram ui components lib for tdesign 1 0 lts tdesign mobile vue https github com tencent tdesign mobile vue vue3 x mobile ui components lib for tdesign 1 0 lts tdesign mobile react https github com tencent tdesign mobile react react mobile ui components lib for tdesign alpha tdesign flutter flutter ui components lib for tdesign in progress repositories for shared repository description tdesign https github com tencent tdesign tdesign main repository and documentation tdesign icons https github com tencent tdesign icons a mono repo for tdesign icons tdesign common https github com tencent tdesign common tdesign common style and utils repositories for out of box starter kits repository description tdesign starter cli https github com tencent tdesign starter cli cli tool for tdesign starter kit tdesign vue starter https github com tencent tdesign vue starter starter kit for tdesign vue ui components tdesign vue next starter https github com tencent tdesign vue next starter starter kit for tdesign vue next ui components tdesign react starter https github com tencent tdesign react starter starter kit for tdesign react ui components tdesign miniprogram starter retail https github com tencent tdesign miniprogram starter retail starter kit for tdesign wechat miniprogram ui components why tdesign before 2019 there were many internal design system and component library projects within tencent centered around product focused decentralized rapid iterations in 2019 tencent established the open source collaboration committee https m thepaper cn yidian promdetail jsp contid 4653692 from tdesign through internal open source collaboration it organized different teams working on similar technology products to collaborate tdesign is the collaborative outcome of frontend and design under tencent s open source collaboration with the aim to jointly build a comprehensive and versatile design system and component library image https user images githubusercontent com 7600149 147126818 0e5a5b2d a833 4107 b654 442f3a1098c5 png development of tdesign tdesign was founded with the principles of open source collaboration from the beginning the collaboration scheme discussion https github com tencent tdesign wiki component design https github com tencent tdesign wiki and api design https github com tencent tdesign wiki including source code are fully open within the company garnering widespread attention from internal developers and designers tdesign follows an equal open and strict policy regardless of the participants roles many participants started by trying out the component library in their personal projects advancing to submit their first issue then their first feature mr and gradually becoming involved in code review and solution formulating tasks eventually turning into core contributors in the past year tdesign has closed 1k issues and conducted 5k code reviews to maintained a weekly iterative release https tdesign tencent com vue components changelog of new versions tdesign currently supports multiple platforms and mainstream front end ui framework desktop versions for vue2 vue3 and react as well as mobile versions for wechat mini programs have been launched as stable versions mobile react and qq mini program versions have been released the alpha versions for internal testing why open source through open sourcing tdesign aims to refine a complete and user friendly component library and cultivate a rich design ecosystem with the help of the community tdesign aspires to maintain ongoing communication with more product designers and developers evolving into a more valuable product open source marks a new beginning for tdesign for tdesign s subsequent development plan please refer to the tdesign upcoming plans https github com tencent tdesign projects 1 features comprehensive support vue 2 https tdesign tencent com vue vue 3 https tdesign tencent com vue next react https tdesign tencent com react for desktop application and vue 3 https tdesign tencent com vue mobile wechat miniprogram https tdesign tencent com miniprogram for mobile application provide a wide variety of design resources including figma adobe xd sketch etc provide auxiliary design tools such as sketch plugin https tdesign tencent com source and support using in codesign https codesign qq com pixso as well image https user images githubusercontent com 7600149 147127234 7961b616 90b6 4197 8676 c041c161ac0d png consistency maintain a unified design values https tdesign tencent com design values and visual style https tdesign tencent com design color helping products maintain a consistent user experience across different platforms during the design and development process consistently defined and implemented apis https tdesign tencent com apis across various tech stacks provide an advantage when building unified cross platform and cross tech stack applications image https user images githubusercontent com 7600149 168031968 267c60f1 efaa 498d a230 a6e0a8093402 png usability extract tencent design experience from various business scenarios and offer universal design guidelines to lower the barriers to entry support extend the design styles by using design token https tdesign tencent com design color header 21 offer tdesign starter kit https tdesign tencent com starter to help developers get started image https user images githubusercontent com 7600149 147127377 6f7e95f6 cfa8 459a 86e0 058c545d34f3 png documentations introduce https tdesign tencent com about introduce contributing https tdesign tencent com about contributing components https tdesign tencent com starter kits https tdesign tencent com starter design guideline https tdesign tencent com design offices read more in the official website of tdesign https tdesign tencent com design guidelines tdesign distills tencent s years of internal design experience into professional design guidelines providing universal design solutions design values https tdesign tencent com design values color https tdesign tencent com design color font https tdesign tencent com design fonts motion https tdesign tencent com design motion icon https tdesign tencent com design icon layout https tdesign tencent com design layout dark mode https tdesign tencent com design dark for more information refer to the guide section of each component such as button https tdesign tencent com vue components button tab design design resources figma https www figma com tencent sketch axure adobe xd https tdesign tencent com source tdesign maker https tdesign tencent com source contributors thanks for all the tdesign contributors div id list style display flex flex wrap wrap a href https github com aandyzhang img width 40px src https avatars githubusercontent com aandyzhang a a href https github com agenal img width 40px src https avatars githubusercontent com agenal a a href https github com zhwachen img width 40px src https avatars githubusercontent com zhwachen a a href https github com realyuyanan img width 40px src https avatars githubusercontent com realyuyanan a a href https github com mrgaogang img width 40px src https avatars githubusercontent com mrgaogang a a href https github com iamber img width 40px src https avatars githubusercontent com iamber a a href https github com amberlwan img width 40px src https avatars githubusercontent com amberlwan a a href https github com andyjxli img width 40px src https avatars githubusercontent com andyjxli a a href https github com zhoulujun img width 40px src https avatars githubusercontent com zhoulujun a a href https github com angelzou img width 40px src https avatars githubusercontent com angelzou a a href https github com anlyyao img width 40px 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redux-toolkit-login-flow | redux toolkit login flow a potentially reusable formalized login flow pattern for crafting web development project why contrary to popular belief never in my career as a software engineer that i build login signin auth page myself i ve always been working on projects where the auth flow is already provided or where login is not required so on this one long weekend during self quarantine period of the outbreak in 2020 https en wikipedia org wiki 2019 e2 80 9320 coronavirus pandemic finally i ve got some spare time to implement my take on it while doing some transcendental explorations on react react router and redux toolkit this project was bootstrapped with create react app https github com facebook create react app using the redux https redux js org and redux toolkit https redux toolkit js org template screenshot of the app artifacts screenshot png as you might have seen this app is built with a very bare minimum if not none of css this is intentional html and javascript can render pretty minimalist can t they the flow i tried to formalize the flow back in the last quarter of 2019 and realised it using this very cool project called plantuml https plantuml com so this is what i think that works for me in 80 of the cases the login flowchart artifacts login flow handwritten png the plantuml source code is available here artifacts login flow puml in the artifacts directory spinning up the development server bash pnpm start you can find other runnable scripts in package json package json author glenn dwiyatcita dwiyatci http tiny cc dwiyatci license wtfpl do what the fuck you want to public license see license txt license txt wtfpl http www wtfpl net wp content uploads 2012 12 wtfpl badge 1 png | login-flow auth react redux-toolkit web-craftmanship | front_end |
J1-Student-Connect | div align center h1 b j1 student connect b h1 p on the way to success there is no trace of lazy men p div h2 about h2 a small project for the mobile developement int3210 course h2 authors h2 p nguy n tu n ngo c uet vnu p p nguy n h u c uet vnu p p bu i thi ngo c uet vnu p p hoa ng phi hu ng uet vnu p p l ng thi thu h ng uet vnu p h2 documents h2 document https docs google com document d 1yzclf4a9hq3iskkciivcavuaxkinug vok54vumfdpa edit figma https www figma com file jblfkki7xgdqsvjferrz5i mobileapp type design node id 3 2 mode design h2 contact h2 p if you have any questions or issues please feel free to contact us at profile of this project owner p p align center thank you for using our project p | front_end |
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aka.org.cn | aka org cn aka information amp technology organization home page pull request is welcome for old fashion team members screenshot 2003 aka web 2003 docs images aka web png http www aka net cn history mar 24 2020 convert all gbk to utf 8 by huan add scripts sh oct 22 2017 fix home page utf 8 encoding more pages need to be converted by huan nov 21 2016 uploaded by taopin | server |
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kit | kit lightweight modular framework for scalable production systems alpha warning kit generator and kit modules code generation is in alpha meaning the api for code generation is subject to change this should not affect users of kit but will affect anyone developing modules or extending them the libs libraries are stable goal the goal of kit is to provide a template for a robust scalable clojure web application it hides common plumbing that is standard across projects via its libs system while exposing code that tends to be customized in the clj new template thanks to integrant and aero the libs are simple skeletons with the bulk of the customization being done in the system configuration edn file quick start kit requires clj new https github com seancorfield clj new installed preferably as a tool clojure ttools install com github seancorfield clj new git tag v1 2 381 as clj new to create a new kit application clojure tclj new create template io github kit clj name yourname app latest versions library latest version io github kit clj kit core clojars project https img shields io clojars v io github kit clj kit core svg https clojars org io github kit clj kit core io github kit clj kit hato clojars project https img shields io clojars v io github kit clj kit hato svg https clojars org io github kit clj kit hato io github kit clj kit metrics clojars project https img shields io clojars v io github kit clj kit metrics svg https clojars org io github kit clj kit metrics io github kit clj kit nrepl clojars project https img shields io clojars v io github kit clj kit nrepl svg https clojars org io github kit clj kit nrepl io github kit clj kit quartz clojars project https img shields io clojars v io github kit clj kit quartz svg https clojars org io github kit clj kit quartz io github kit clj kit redis clojars project https img shields io clojars v io github kit clj kit redis svg https clojars org io github kit clj kit redis io github kit clj kit repl clojars project https img shields io clojars v io github kit clj kit repl svg https clojars org io github kit clj kit repl io github kit clj kit selmer clojars project https img shields io clojars v io github kit clj kit selmer svg https clojars org io github kit clj kit selmer io github kit clj kit sql clojars project https img shields io clojars v io github kit clj kit sql svg https clojars org io github kit clj kit sql io github kit clj kit sql conman clojars project https img shields io clojars v io github kit clj kit sql conman svg https clojars org io github kit clj kit sql conman io github kit clj kit sql hikari clojars project https img shields io clojars v io github kit clj kit sql hikari svg https clojars org io github kit clj kit sql hikari io github kit clj kit sql migratus clojars project https img shields io clojars v io github kit clj kit sql migratus svg https clojars org io github kit clj kit sql migratus io github kit clj kit postgres clojars project https img shields io clojars v io github kit clj kit postgres svg https clojars org io github kit clj kit postgres io github kit clj kit mysql clojars project https img shields io clojars v io github kit clj kit mysql svg https clojars org io github kit clj kit mysql io github kit clj kit xtdb clojars project https img shields io clojars v io github kit clj kit xtdb svg https clojars org io github kit clj kit xtdb io github kit clj kit generator clojars project https img shields io clojars v io github kit clj kit generator svg https clojars org io github kit clj kit generator io github kit clj lein template clojars project https img shields io clojars v io github kit clj lein template svg https clojars org io github kit clj lein template io github kit clj deps template clojars project https img shields io clojars v io github kit clj lein template svg https clojars org io github kit clj deps template profiles default libs included with no profile specified kit core kit undertow additional profiles xtdb adds the kit xtdb lib hato adds the kit hato lib metrics adds the kit metrics lib quartz adds the kit quartz lib redis adds the kit redis lib selmer adds the kit selmer lib nrepl adds the kit nrepl lib socket repl adds the kit repl lib sql adds the default sql libraries kit sql conman kit sql migratus and kit postgres libs conman adds the kit sql conman lib hikari adds the kit sql hikari lib migratus adds the kit sql migratus lib mysql adds the kit sql general and kit mysql libs full adds the libs kit xtdb kit hato kit metrics kit quartz kit redis kit selmer kit repl kit sql conman kit postgres and kit sql migratus libs kit core basic utility functions used by some other libs kit xtdb simple binding to connect to a xtdb https xtdb com database node kit hato http client using hato https github com gnarroway hato kit nrepl nrepl https github com nrepl nrepl component for use in a running system e g to connect to a production repl kit metrics configurable metrics using iapetos https github com clj commons iapetos kit quartz scheduler using cronut https github com troy west cronut as an integrant binding for quartz http www quartz scheduler org exposes the cronut api simply some extensions for aero and utilities kit redis an extension of core cache https github com clojure core cache for redis via carmine https github com ptaoussanis carmine kit repl socket repl integrant binding for use in a running system e g to connect to a production repl kit selmer templating configuration with selmer https github com yogthos selmer kit sql deprecated use kit sql conman and kit sql migratus pulls in both of these as generic sql integrant binding uses conman https github com luminus framework conman next jdbc https github com seancorfield next jdbc hugsql https www hugsql org and migratus https github com yogthos migratus directly or implicitly kit sql conman uses conman https github com luminus framework conman next jdbc https github com seancorfield next jdbc hugsql https www hugsql org kit sql hikari general sql layer just contains connection pooling via hikari cp https github com tomekw hikari cp and jdbc wrapper via next jdbc https github com seancorfield next jdbc kit sql migratus uses migratus https github com yogthos migratus for sql migrations kit postgres lib with data bindings and utilities for working with postgres kit mysql lib with data bindings and utilities for working with mysql8 kit undertow server binding via ring undertow adapter https github com luminus framework ring undertow adapter build tool support presently only clojure deps is supported however there are plans to add leiningen support documentation documentation can be found here https kit clj github io emacs integration an emacs package https github com jpe90 emacs clj deps new is available which provides a magit style interface to clj new and deps new and provides a command to create kit web applications inspiration and thanks to integrant https github com weavejester integrant as the basis of the project aero https github com juxt aero for powerful configuration used throughout re frame template https github com day8 re frame template for code used directly in kit template luminus framework https luminusweb com from which the initial project that kit s predecessor was built upon license copyright 2021 released under the mit license | clojure framework web integrant kit-clj | front_end |
npcgpt | npcgpt writeup https medium com sean skimmer npc gpt 3f4cb5272773 leveraging large language models for video games and npcs this proof of concept is built out for the game stardew valley https www stardewvalley net the project is made up of 3 parts described below part 1 character generation to generate dynamic and unique npc s the first model generates a short character bio the model is based on openai s open source gpt2lmheadmodel https huggingface co docs transformers model doc gpt2 transformers gpt2lmheadmodel the model was fine tuned using sample character bios that were generated using similar formatting and description styles as the stardew valley villager wiki pages https stardewvalleywiki com villagers the sample bios used for training data can be found at data character bios csv the generated character bio is then cleaned and processed to be used as input for the dialogue model part 2 dialogue model the cleaned personalities generated by the model above are fed into the dialogue model to create conversations that are both relevant to the game and personality for this step the knowledge base of objects in the game was created to ensure the dialogue surrounded relevant items mobs and locations training data was created with the chatgpt api https openai com blog introducing chatgpt and whisper apis created by openai using prompts that returned item definitions quests and general dialogue this replaced the original method which used the original game dialogue scraped with videogamedialoguecorpuspublic https github com seannyd videogamedialoguecorpuspublic as the original dialogue was not comprehensive enough to achieve substantial results multiple models were trained with guidance from this medium article https medium com huggingface how to build a state of the art conversational ai with transfer learning 2d818ac26313 using dialogpt https huggingface co microsoft dialogpt medium text hey my name is mariama 21 how are you 3f and gpt2 https huggingface co gpt2 as base models the outputs of this model are run through part 3 to determine if there is intent related to a conversation part 3 rule based named entity recognition for intent recognition to capture the transactional intention of dialogue with the npc two spacy matchers https spacy io api matcher are used to identify and pull the relevant information from the dialogue for example if the user asks the npc for a quest the npc might give the user an item quest or a mob related quest the matcher rules can identify that a quest has been given to the user and extract the target items or mobs the quantity requested and the potential reward offered to the user upon completion of the request this information is used to dynamically implement the transactions in the game allowing for a more robust and complete user experience | ai |
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devpackages | modern web development workflow build status https img shields io travis com digitoimistodude devpackages svg style flat square https travis ci com digitoimistodude devpackages github release https img shields io github release digitoimistodude devpackages svg style flat square https github com digitoimistodude devpackages releases used by digitoimisto dude oy this repository includes gulp http gulpjs com and npm related files for starting a new project these files are specifically meant for development on dudestack https github com digitoimistodude dudestack modern html5 boilerplate https github com digitoimistodude modern html5 boilerplate and air light starter theme https github com digitoimistodude air light these tools are compatible with vscode https github com ronilaukkarinen vscode settings and sublime text https github com digitoimistodude sublime settings table of contents 1 features features 2 usage usage 3 debuggers debuggers 4 contributing contributing features 1 browsersync https github com browsersync browser sync time saving synchronised browser testing 2 gulp https github com gulpjs gulp automate and enhance your workflow 3 stylefmt https github com morishitter stylefmt gulp stylefmt https github com morishitter gulp stylefmt stylefmt is a tool that automatically formats stylesheets extending stylelint functionality 4 stylelint https github com stylelint stylelint gulp stylelint https github com olegskl gulp stylelint configurable tool for writing clean and consistent scss 5 eslint https github com eslint eslint gulp eslint https github com adametry gulp eslint find and fix problems in your javascript code 6 php codesniffer https github com squizlabs php codesniffer gulp phpcs https github com justblackbird gulp phpcs detects violations of a defined set of coding standards usage make sure linters are installed for gulp tutorial below debuggers best way to install phpcs and phpcbf is to clone them to projects link them to usr local bin and set paths with phpcs phpcbf config set installed paths path to wpcs path to phpcompatibility please note currently this repo is bundled with wordpress starter theme air https github com digitoimistodude air light and dudestack https github com digitoimistodude dudestack with automated scripts but you can use devpackages as stand alone as well like this 1 clone this repo and add files to your project folder edit them according to your project 2 update packages npm check updates u if you don t have npm check updates installed run sudo npm install g npm check updates 3 proceed with the updates npm update 4 run gulp watch and have fun debuggers devpackages comes with php codesniffer https github com squizlabs php codesniffer for php files stylelint https github com stylelint stylelint for scss css files and eslint https github com eslint eslint for js files built inside gulpfile js please note you need to configure global versions of these separately here s how for gulp php codesniffer needs to be installed under usr local bin phpcs with wordpress coding standards https github com wordpress coding standards wordpress coding standards for php debuggers to work properly in gulp if you don t want to use phpcs with gulp you can disable it by commenting out or deleting line gulp watch phpsrc phpcs the golden rule here is to make sure the commands stylelint eslint and phpcs work from command line how to install for gulp 1 mkdir p projects cd projects git clone b master depth 1 https github com squizlabs php codesniffer git phpcs 2 git clone b master https github com phpcompatibility phpcompatibility 3 git clone b master depth 1 https github com wordpress coding standards wordpress coding standards git wpcs 4 please note replace yourusername name with your actual user name sudo ln s users yourusername projects phpcs bin phpcs usr local bin phpcs 5 sudo chmod x usr local bin phpcs 6 please note replace yourusername name with your actual user name phpcs config set installed paths users yourusername projects wpcs users yourusername projects phpcompatibility 7 test your standards with phpcs i it should display something like this bash phpcs i the installed coding standards are pear zend psr2 mysource squiz psr1 psr12 phpcompatibility wordpress wordpress extra wordpress docs and wordpress core 8 npm i stylelint eslint g 9 check that other linters work stylelint v eslint v for your editor it s also best to have all stylelint eslint phpcs jscs jshint living inside your editor we think visual studio code https github com ronilaukkarinen vscode settings is best for this check out the plugins inside vscode settings repository https github com ronilaukkarinen vscode settings to make sure everything is installed after this you can run gulp a okay variables declared as map are forcely inlined see this issue https github com morishitter stylefmt issues 331 solve by using up to date fork of vscode stylefmt https github com ronilaukkarinen vscode stylefmt contributing if you d like to contribute to this repository or test out the packages please follow these steps 1 fork this repository 2 clone your fork 3 get the test data https files servepics com content 1649685325 zip and unpack it to your devpackages folder 4 run npm install and gulp unit tests for stylelint packages bash cd path to repo mkdir p content mkdir p content themes content themes themename content themes themename sass echo charset utf 8 body background f00 color red important font size 2rem media max width 600px border 2px solid red content themes themename sass global scss npm i gulp stylelint | workflow gulp javascript | front_end |
alluxio | logo docs resources alluxio logo png alluxio https www alluxio io slack https img shields io badge slack alluxio community blue svg logo slack https www alluxio io slack release https img shields io github release alluxio alluxio all svg https www alluxio io download docker pulls https img shields io docker pulls alluxio alluxio svg https hub docker com r alluxio alluxio documentation https img shields io badge docs reference blue svg https www alluxio io docs openssf scorecard https api securityscorecards dev projects github com alluxio alluxio badge https api securityscorecards dev projects github com alluxio alluxio twitter follow https img shields io twitter follow alluxio svg label follow style social https twitter com intent follow screen name alluxio license https img shields io github license alluxio alluxio svg https github com alluxio alluxio blob master license what is alluxio alluxio https www alluxio io formerly known as tachyon is a virtual distributed storage system it bridges the gap between computation frameworks and storage systems enabling computation applications to connect to numerous storage systems through a common interface read more about alluxio overview https docs alluxio io os user stable en overview html the alluxio project originated from a research project called tachyon at amplab uc berkeley which was the data layer of the berkeley data analytics stack bdas https amplab cs berkeley edu bdas for more details please refer to haoyuan li s phd dissertation alluxio a virtual distributed file system https www2 eecs berkeley edu pubs techrpts 2018 eecs 2018 29 html who uses alluxio alluxio is used in production to manage petabytes of data in many leading companies with the largest deployment exceeding 3 000 nodes you can find more use cases at powered by alluxio https www alluxio io powered by alluxio or visit our first community conference data orchestration summit https www alluxio io data orchestration summit 2019 to learn from other community members who owns and manages alluxio project alluxio open source foundation is the owner of alluxio project project operation is done by alluxio project management committee pmc you can checkout more details in its structure and how to join alluxio pmc here https github com alluxio alluxio wiki alluxio project management committee pmc community and events please use the following to reach members of the community alluxio community slack channel https www alluxio io slack post your questions here if you seek for help for general questions or issues using alluxio special interest groups sig for alluxio users and developers contributing community events upcoming online office hours meetups and webinars https www alluxio io events meetup groups global online meetup https www meetup com alluxio global online meetup bay area meetup http www meetup com alluxio new york meetup https www meetup com alluxio open source new york meetup beijing alluxio meetup https www meetup com meetup group ilmbzghs austin meetup https www meetup com cloud data orchestration austin alluxio twitter https twitter com alluxio alluxio youtube channel https www youtube com channel ucpibqsajhwqyplyhke4riga alluxio mailing list https groups google com forum fromgroups forum alluxio users download alluxio binary download prebuilt binaries are available to download at https www alluxio io download docker download and start an alluxio master and a worker more details can be found in documentation https docs alluxio io os user stable en deploy running alluxio on docker html console create a network for connecting alluxio containers docker network create alluxio nw create a volume for storing ufs data docker volume create ufs launch the alluxio master docker run d net alluxio nw p 19999 19999 name alluxio master v ufs opt alluxio underfsstorage alluxio alluxio master launch the alluxio worker export alluxio worker ramdisk size 1g docker run d net alluxio nw shm size alluxio worker ramdisk size name alluxio worker v ufs opt alluxio underfsstorage e alluxio java opts dalluxio worker ramdisk size alluxio worker ramdisk size dalluxio master hostname alluxio master alluxio alluxio worker macos homebrew console brew install alluxio quick start please follow the guide to get started https docs alluxio io os user stable en getting started html to run a simple example with alluxio report a bug to report bugs suggest improvements or create new feature requests please open a github issue https github com alluxio alluxio issues if you are not sure whether you run into bugs or simply have general questions with respect to alluxio post your questions on alluxio slack channel www alluxio io slack depend on alluxio alluxio project provides several different client artifacts for external projects to depend on alluxio client artifact alluxio shaded client is recommended generally for a project to use alluxio client the jar of this artifact is self contained including all dependencies in a shaded form to prevent dependency conflicts and thus larger than the following two artifacts artifact alluxio core client fs provides alluxio java file system api https docs alluxio io os user stable en api java api html alluxio java api to access all alluxio specific functionalities this artifact is included in alluxio shaded client artifact alluxio core client hdfs provides hdfs compatible file system api https docs alluxio io os user stable en api java api html hadoop compatible java client this artifact is included in alluxio shaded client here are examples to declare the dependecies on alluxio shaded client using maven xml dependency groupid org alluxio groupid artifactid alluxio shaded client artifactid version 2 6 0 version dependency contributing contributions via github pull requests are gladly accepted from their original author along with any pull requests please state that the contribution is your original work and that you license the work to the project under the project s open source license whether or not you state this explicitly by submitting any copyrighted material via pull request email or other means you agree to license the material under the project s open source license and warrant that you have the legal authority to do so for a more detailed step by step guide please read how to contribute to alluxio https docs alluxio io os user stable en contributor contributor getting started html for new contributor please take two new contributor tasks https github com alluxio new contributor tasks for advanced feature requests and contributions alluxio core team is hosting regular online meetings with community users and developers to iterate the project in two special interest groups alluxio and ai workloads e g running tensorflow pytorch on alluxio through the posix api checkout the meeting notes https docs google com spreadsheets d 1olpriiukgjmuzj 6cltjyvjptgpntwkfhhzx16tyndq alluxio and presto workloads e g running presto on alluxio checkout the meeting notes https docs google com spreadsheets d 1v fxqfg oj3b1zwsgbrwvuthfvjl3pq6uxgal xvfqa subscribe our public calendar https calendar google com calendar embed src alluxio com g9ec8agk27baqu2nu692ft1m3s 40group calendar google com ctz america 2flos angeles to join us useful links alluxio website https www alluxio io downloads https www alluxio io download releases and notes https www alluxio io download releases documentation https www alluxio io docs | alluxio memory-speed hadoop spark presto tensorflow data-analysis data-orchestration virtual-distributed-filesystem | ai |
Full-Control | this repository covers the development of an smarthome web application built with nodejs express for the backend and angular 4 for the frontend using a raspberry pi the webserver is serving the angular static files and listening to rest api calls with this sample app you can control the light bulbs and airconditioners | server |
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fx3 | fx3 rtos scope this is a new rtos developed from the ground up with two main goals being easy to learn and review and being efficient in terms of resource usage it presentely targets arm cortex m3 4 microcontrollers the examples use inexpensive stm32 discovery www st com stm32discovery pr boards license apache license version 2 0 pre requisites you will need arm cmsis 4 5 vendor drivers for stm32 you ll need the stm32cubef4 http www st com web en catalog tools pf259243 and stm32cubef3 http www st com web en catalog tools pf260613 drivers for kinetis you ll nedd the kinetis sdk http kex nxp com en welcome a compiler fx3 is developed using gcc arm embedded https launchpad net gcc arm embedded version 5 2 1 it can be compiled with clang 3 8 http clang llvm org but the gnu arm linker and support libraries are required gnu make version 4 0 or later universal ctags https ctags io there is a bug in the widely available ctags 5 8 where tags with relative paths are not generated correctly it works fine for recursive build but not for the new build cpputest https cpputest github io have cpputest home environment variable point to it the libraries need to be expanded into a folder pointed to by the embedded environmnent variable see config mk for details the build system is os agnostic tested on windows and linux other tools for debugging the discovery boards you ll need st link http www st com web catalog tools fm146 cl1984 sc724 ss1677 pf251168 drivers and utilities for other boards i recommend the excellent segger j link https www segger com jlink debug probes html for their versatility and cross platform support my main debugger is winidea open http www isystem com download winideaopen version 9 2 256 and i m also exploring segger ozone https www segger com ozone html building examples assuming you have set up the environment you should be able to run make from the top level folder documentation plans design documents are in the doc folder references books the definitive guide to arm cortex m3 and cortex m4 processors third edition by joseph yiu programming pearls second edition by jon bentley happy hacking florin signbit net | os |
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defects4j | defects4j version 2 0 0 build status https travis ci com rjust defects4j svg branch master https travis ci com rjust defects4j defects4j is a collection of reproducible bugs and a supporting infrastructure with the goal of advancing software engineering research contents of defects4j the projects comment do not edit generated by framework util create bugs table pl defects4j contains 835 bugs plus 29 deprecated bugs from the following open source projects identifier project name number of active bugs active bug ids deprecated bug ids chart jfreechart 26 1 26 none cli commons cli 39 1 5 7 40 6 closure closure compiler 174 1 62 64 92 94 176 63 93 codec commons codec 18 1 18 none collections commons collections 4 25 28 1 24 compress commons compress 47 1 47 none csv commons csv 16 1 16 none gson gson 18 1 18 none jacksoncore jackson core 26 1 26 none jacksondatabind jackson databind 112 1 112 none jacksonxml jackson dataformat xml 6 1 6 none jsoup jsoup 93 1 93 none jxpath commons jxpath 22 1 22 none lang commons lang 64 1 3 65 2 math commons math 106 1 106 none mockito mockito 38 1 38 none time joda time 26 1 20 22 27 21 due to behavioral changes introduced under java 8 some bugs are no longer reproducible hence defects4j distinguishes between active and deprecated bugs active bugs can be accessed through active bugs csv deprecated bugs are removed from active bugs csv but their metadata is retained in the project directory deprecated bugs can be accessed through deprecated bugs csv which also details when and why a bug was deprecated we do not re enumerate active bugs because publications using defects4j artifacts usually refer to bugs by their specific bug id the bugs each bug has the following properties issue filed in the corresponding issue tracker and issue tracker identifier mentioned in the fixing commit message fixed in a single commit minimized the defects4j maintainers manually pruned out irrelevant changes in the commit e g refactorings or feature additions fixed by modifying the source code as opposed to configuration files documentation or test files a triggering test exists that failed before the fix and passes after the fix the test failure is not random or dependent on test execution order the b uggy and f ixed program revisions are labelled with id b and id f respectively id is an integer setting up defects4j requirements java 1 8 git 1 9 svn 1 8 perl 5 0 12 defects4j version 1 x and 0 x required java 1 7 java version all bugs have been reproduced and triggering tests verified using the latest version of java 1 8 using a different version of java might result in unexpected failing tests on a fixed program version timezone defects4j generates and executes tests in the timezone america los angeles if you are using the bugs outside of the defects4j framework set the tz environment variable to america los angeles and export it perl dependencies all required perl modules are listed in cpanfile https github com rjust defects4j blob master cpanfile on many unix platforms these required perl modules are installed by default if this is not the case see instructions below for how to install them steps to set up defects4j 1 clone defects4j git clone https github com rjust defects4j 2 initialize defects4j download the project repositories and external libraries which are not included in the git repository for size purposes and to avoid redundancies if you do not have cpanm installed use cpan or a cpan wrapper to install the perl modules listed in cpanfile cd defects4j cpanm installdeps init sh 3 add defects4j s executables to your path export path path path2defects4j framework bin 4 check installation defects4j info p lang on some platforms such as windows you might need to use perl fullpath defects4j where these instructions say to use defects4j using defects4j example commands 1 get information for a specific project commons lang defects4j info p lang 2 get information for a specific bug commons lang bug 1 defects4j info p lang b 1 3 checkout a buggy source code version commons lang bug 1 buggy version defects4j checkout p lang v 1b w tmp lang 1 buggy 4 change to the working directory compile sources and tests and run tests cd tmp lang 1 buggy defects4j compile defects4j test 5 the scripts in framework test framework test are examples of how to use defects4j which you might find useful as inspiration when you are writing your own scripts that use defects4j command line interface defects4j command use framework bin defects4j http defects4j org html doc defects4j html to execute any of the following commands command description info http defects4j org html doc d4j d4j info html view configuration of a specific project or summary of a specific bug env http defects4j org html doc d4j d4j env html print the environment of defects4j executions checkout http defects4j org html doc d4j d4j checkout html checkout a buggy or a fixed project version compile http defects4j org html doc d4j d4j compile html compile sources and developer written tests of a buggy or a fixed project version test http defects4j org html doc d4j d4j test html run a single test method or a test suite on a buggy or a fixed project version mutation http defects4j org html doc d4j d4j mutation html run mutation analysis on a buggy or a fixed project version coverage http defects4j org html doc d4j d4j coverage html run code coverage analysis on a buggy or a fixed project version monitor test http defects4j org html doc d4j d4j monitor test html monitor the class loader during the execution of a single test or a test suite bids http defects4j org html doc d4j d4j bids html print the list of active or deprecated bug ids for a specific project pids http defects4j org html doc d4j d4j pids html print a list of available project ids export http defects4j org html doc d4j d4j export html export version specific properties such as classpaths directories or lists of tests query http defects4j org html doc d4j d4j query html query the metadata to generate a csv file of requested information for a specific project export version specific properties use defects4j export p property name o output file in the working directory to export a version specific property property description classes modified classes modified by the bug fix classes relevant classes loaded by the jvm when executing all triggering tests cp compile classpath to compile and run the project cp test classpath to compile and run the developer written tests dir src classes source directory of classes relative to working directory dir bin classes target directory of classes relative to working directory dir src tests source directory of tests relative to working directory dir bin tests target directory of test classes relative to working directory tests all list of all developer written test classes tests relevant list of relevant tests classes a test class is relevant if when executed the jvm loads at least one of the modified classes tests trigger list of test methods that trigger expose the bug export project specific metadata use defects4j query p pid q field list o output file d a to generate a csv file containing a set of requested metadata for each bug in a specific project by default defects4j query returns a list of active bug ids for a project to request specific metadata the q flag should be provided with a comma separated list of variables from the list below for example defects4j query p chart q report id report url will provide the a list of all active bug ids along with the bug report id and bug report url for each property description bug id assigned bug ids included in all results project id assigned project id project name original project name project build file location of the defects4j build file for the project project vcs version control system used by the project project repository location of the project repository project bugs csv location of the csv containing information on that bug revision id buggy commit hashes for the buggy version of each bug revision id fixed commit hashes for the fixed version of each bug revision date buggy date of the buggy commit for each bug revision date fixed date of the fixed commit for each bug report id bug report id from the version tracker for each bug report url bug report url from the version tracker for each bug classes modified classes modified by the bug fix classes relevant src source classes loaded by the jvm when executing all triggering tests classes relevant test test classes loaded by the jvm when executing all triggering tests tests relevant list of relevant tests classes a test class is relevant if when executed the jvm loads at least one of the modified classes tests trigger list of test methods that trigger expose the bug tests trigger cause list of test methods that trigger expose the bug along with the root cause deprecated version for deprecated bugs only version of defects4j where a bug was deprecated deprecated reason for deprecated bugs only reason for deprecation by default defects4j query returns information on active bugs the d flag returns information only on deprecated bugs while the a flag returns information for all active and deprecated bugs test execution framework the test execution framework for generated test suites framework bin provides the following scripts script description defects4j http defects4j org html doc defects4j html main script described above gen tests http defects4j org html doc gen tests html generate test suites using evosuite or randoop run bug detection http defects4j org html doc run bug detection html determine the real fault detection rate run mutation http defects4j org html doc run mutation html determine the mutation score run coverage http defects4j org html doc run coverage html determine code coverage ratios statement and branch coverage mining and contributing additional bugs to defects4j we welcome your contributions to defects4j the bug mining readme framework bug mining readme md details the bug mining process additional resources scripts built on defects4j fault localization fl scripts and annotations for evaluating fl techniques fl eval automated program repair apr scripts and annotations for evaluating apr techniques apr eval patches generated with the nopol jgenprog and jkali apr systems apr patches spirals repair actions and patterns for defects4j v1 2 0 d4j dissection fl eval https bitbucket org rjust fault localization data apr eval https github com laser umass automatedrepairapplicabilitydata apr patches spirals https github com spirals team defects4j repair d4j dissection http program repair org defects4j dissection publications defects4j a database of existing faults to enable controlled testing studies for java programs ren just darioush jalali and michael d ernst issta 2014 download issta14 are mutants a valid substitute for real faults in software testing ren just darioush jalali laura inozemtseva michael d ernst reid holmes and gordon fraser fse 2014 download fse14 challenges in using search based test generation to identify real faults in mockito gregory gay ssbse 2016 download ssbse16 detecting real faults in the gson library through search based unit test generation gregory gay ssbse 2018 download ssbse18 defects4j as a challenge case for the search based software engineering community gregory gay and ren just ssbse 2020 download ssbse20 issta14 https people cs umass edu rjust publ defects4j issta 2014 pdf fse14 https people cs umass edu rjust publ mutants real faults fse 2014 pdf ssbse16 https greg4cr github io pdf 16mockito pdf ssbse18 https greg4cr github io pdf 18gson pdf ssbse20 https greg4cr github io pdf 20d4j pdf more publications https scholar google com scholar q defects4j implementation details documentation for any script or module is available as html documentation htmldocs htmldocs http defects4j org html doc index html the directory structure of defects4j is as follows defects4j project repos the version control repositories of the provided projects major the major mutation framework framework libraries and executables of the core test execution and bug mining frameworks bin command line interface to defects4j bug mining bug mining framework core the modules of the core framework lib libraries used in the core framework util util scripts used by defects4j projects project specific resource files test scripts to test the framework versioning information defects4j uses a semantic versioning scheme major minor patch change major minor patch addition deletion of bugs x new upgraded internal or external tools x fixes and documentation changes x license mit license see license txt https github com rjust defects4j blob master license txt for more information | defects4j java perl | server |
iris | o o os o s sso oyo os o o yhyssss o o sy so hhhys ossyhdhsoo so sdhhds syo ooossyyyys ss oshmdd ssso oyhoymmd o smmmymm ymdmo o odm oosd so sysm s ysso osyohm dh hs ssyy hms shm syys odm ssym ooosyyyo hmhsyhm yhhhhhs ymysyddo d8 d8 ohho mssymdo 8p 8p s ysshmdo ooooss yyhdd 88b 88bd88b 88b d888b ssssy ydddm 88p 88p 88p 8b hdddh d88 d88 d88 8b hddm d88 d88 d88 888p dmmn mnns dnn ynh iris https github com vimeo iris is the design system that powers vimeo s web apps many components and tokens are viewable in storybook https vimeo github io iris sb main a documentation website with more comprehensive information as well as pattern guidance beyond tokens and components is forthcoming | os |
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Skywork-MM | skywork mm empirical study towards building an effective multi modal large language model | ai |
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Quant_stock | quant stock stock analysis prediction model using machine learning using the impact between different out of the market factors weather etc and the stock prices architecture diagram diagram png raw true architecture diagram models used there are three ml model that are being implemented a simple feedforward neural network a recurrent neural network with lstm long short term memory a convolutional neural network accuracy measurements the pipeline implemented is using backtrader https www backtrader com to implement backtesting in order to test each individual strategy in the future it is worthwhile to try using a genetic algorithm to better figure the accuracy of the model usage there are three main usages for this project run python driver py t model name to train run python driver py b model name to backtest the model | stock-analysis prediction-model machine-learning backtrader tensorflow stock-prediction quant-stock | ai |
web-dev-resources | thanks for checking out the web dev resources if you have a suggestion that would make this better please fork the repo and create a pull request or simply open an issue with the tag enhancement thanks again project shields i m using markdown reference style links for readability reference links are enclosed in brackets instead of parentheses see the bottom of this document for the declaration of the reference variables for contributors url forks url etc this is an optional concise syntax you may use https www markdownguide org basic syntax reference style links project logo br p align center a href https https github com karantondare web dev resources img src https user images githubusercontent com 64483658 115106433 70aec980 9f82 11eb 8850 5a11a2b87752 png alt logo width 240 height 240 a h3 align center best web dev resources h3 p align center find resources to become full stack web developer br p p table of contents details open open summary table of contents summary ol li a href about the project about the project a li li a href getting started getting started a li li a href programs and classes programs and classes a li li a href learn html learn html a li li a href learn css learn css a li li a href learn git learn git a li li a href learn javascript learn javascript a li li a href learn typescript learn typescript a li li a href learn reactjs learn reactjs a li li a href learn nodejs learn nodejs a li li a href learn apis learn api a li li a href learn database learn database a li li a href learn authentication learn authentication a li ol details about the project about the project details open open summary about the project summary br hello thank you for checking out a href https https github com karantondare web dev resources web dev resources a these are the resources that i found which helped me learn full stack web development note some of the links are for the paid courses any of the attached links are not affiliated details getting started getting started details open open summary getting started summary br the list below isn t meant to be exclusive it s more so a collection of links that have helped me out along the way and can hopefully help you as you ll see i ve focused on javascript react and node js there is also a wealth of information on interview prep and applying to jobs 2021 web developer roadmap https roadmap sh brad traversy s youtube video on what to learn web development in 2021 a practical guide https www youtube com watch v vfgw0qiy2i0 ab channel traversymedia coursera course not cs specific learning how to learn https www coursera org learn learning how to learn teaching yourself computer science https teachyourselfcs com details best bookmarks i have what is the single most useful cs bookmark you have details open open br build your own x https github com danistefanovic build your own x dev docs https devdocs io details programs and curriculums programs and classes details open open summary programs and classes summary br bootcamps the frontend developer career path https scrimba com learn frontend the web developer bootcamp by colt steele https www udemy com course the web developer bootcamp programs the odin project http www theodinproject com freecodecamp https www freecodecamp com the essential web developer course https open appacademy io free access to their various curriculums full stack open by university of helsinki https fullstackopen com en learn to build fullstack app using mern stack details learn html learn html details open open summary html resources summary br html5 full tutorial w3schools https www w3schools com html learn html and css https www internetingishard com html5 introduction edx https www edx org course html5 introduction w3cx html5 0x 0 html cheat sheet https websitesetup org html5 cheat sheet html best practices https github com hail2u html best practices details learn css learn css details open open summary css resources summary br the responsive web design bootcamp https scrimba com learn responsive learn html and css https www internetingishard com html and css tutorial for 2021 complete crash course https www youtube com watch v d h8l5hgw w ab channel designcourse 100 days of css https 100dayscss com css games flexbox froggy https flexboxfroggy com css grid garden https cssgridgarden com css dinner https flukeout github io css cheat sheet https websitesetup org css3 cheat sheet blog posts and articles the css cascade https wattenberger com blog css cascade details learn git learn git details open open summary git resources summary br git and github for beginners crash course https www youtube com watch v rgoj5yh7evk t 5s ab channel freecodecamp org learn git branching https learngitbranching js org details learn javascript learn javascript details open open summary javascript resources summary br freecodecamp s javascript playlist on youtube https www youtube com playlist list plwkjhjtqvablede3 za8h3ao2rxar q2v mdn s javascript tutorial https developer mozilla org en us docs web javascript scrimba s the javascript bootcamp https scrimba com learn javascript wes bos s beginner javascript course https wesbos com javascript javascript understanding the weird parts https www udemy com course understand javascript javascript info https javascript info javsscript projects 30 day vanilla js coding challenge https javascript30 com 100 javascript projects for beginners https jsbeginners com javascript projects for beginners build 15 javascript projects vanilla javascript course https www youtube com watch v 3phxvlpokf4 ab channel freecodecamp org javascript data structures and algorithms javascript algorithms and data structures https github com trekhleb javascript algorithms data structures algorithms javascript https www udemy com course data structures algorithms javascript coding challenges edabit https edabit com challenges javascript exercism https exercism io tracks javascript codewars https www codewars com books eloquent javascript https eloquentjavascript net you dont know js https github com getify you dont know js learning javascript design patterns https addyosmani com resources essentialjsdesignpatterns book blog posts and articles a study plan to cure javascript fatigue https www freecodecamp org news a study plan to cure javascript fatigue 8ad3a54f2eb1 understanding closures in javascript https blog bitsrc io a beginners guide to closures in javascript 97d372284dda callback hell http callbackhell com details learn typescript learn typescript details open open summary typescript resources summary br typescript course for beginners 2021 learn typescript from scratch https www youtube com watch v bwulxph8ids t 6181s typescript playlist by net ninja https www youtube com playlist list pl4cuxegkcc9gugr39q yd6v bsymwkpui no bs ts by jack herrington https www youtube com playlist list plnqp92 exzbjyfrpezdo2eapvu0goj09n typescript the complete developer s guide https www udemy com course typescript the complete developers guide react typescript cheatsheet https github com typescript cheatsheets react typescript exercise https typescript exercises github io exercise 1 file 2findex ts books typescript in 50 lessons https typescript book com programming typescript making your javascript applications scale https www amazon in programming typescript boris cherny dp 1492037656 effective typescript 62 specific ways to improve your typescript https www amazon in effective typescript dan vanderkam dp 1492053740 tackling typescript upgrading from javascript https exploringjs com tackling ts blog posts and articles why you should choose typescript over javascript https serokell io blog why typescript typescript generics for people who gave up on understanding generics https www robinwieruch de react testing library here is what every react developer needs to know about typescript part 1 https blog dastasoft com posts heres what every react developer needs to know about typescript react query and typescript https tkdodo eu blog react query and type script in depth look at typescript generics part 1 intro to generics https itnext io in depth look at typescript generics part 1 intro to generics 7ddc72dcfcea in depth look at typescript generics part 2 advanced inference https itnext io in depth look at typescript generics part 2 advanced inference 5c75638ee6bf details learn javascript learn reactjs details open open summary reactjs summary br full react course 2020 learn fundamentals hooks context api react router custom hooks https www youtube com watch v 4uzrstqkcw4 t 5s ab channel freecodecamp org freecodecamp s react playlist on youtube https www youtube com playlist list plwkjhjtqvabkardmazoartnz1amwnwmvc epic react by kent c dodds https epicreact dev 70 open source clones of sites like airbnb tiktok netflix spotify etc https gourav io clone wars react testing how to use react testing library tutorial https www robinwieruch de react testing library kent c dodds blogs on testing https kentcdodds com blog q testing books pure react by dave cedia https daveceddia com pure react learning react 2nd edition https www oreilly com library view learning react 2nd 9781492051718 blog posts and articles thinking in react hooks https wattenberger com blog react hooks why react hooks https ui dev why react hooks flow control in react https reacttraining com blog flow control in react a mostly complete guide to react rendering behavior https blog isquaredsoftware com 2020 05 blogged answers a mostly complete guide to react rendering behavior typescript react why i don t use react fc https fettblog eu typescript react why i dont use react fc not all components are created equal https formidable com blog 2021 react components usestate lazy initialization and function updates https kentcdodds com blog use state lazy initialization and function updates state colocation will make your react app faster https kentcdodds com blog state colocation will make your react app faster should i usestate or usereducer https kentcdodds com blog should i usestate or usereducer details learn javascript learn nodejs details open open summary nodejs summary br the complete node js developer course https www udemy com course the complete nodejs developer course 2 traversy media s nodejs playlist https www youtube com playlist list plillgf rfqbz2ybcod2oaabw2p7ws8cwu fullstack projects build social media app by javascript mastery https www youtube com playlist list pl6qrej8te1p7vswhrmf3d3xt4v6 srkhu mern ecommerce from scratch https www udemy com course mern ecommerce blog posts and articles the node js way understanding error first callbacks http fredkschott com post 2014 03 understanding error first callbacks in node js how node js middleware works https medium com selvaganesh93 how node js middleware works d8e02a936113 details | javascript react css html typescript nodejs mongodb express | front_end |
ironman | ironman this is final project of embedded system design ii in pitts ece actually this course is about android programming and our goal is to develop a video player which could dimming to save power | os |
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stm32f3-tiny-rtos | a tiny rtos simply explained this is a tiny real time operating system written for stm32f3 microcontrollers https www st com en microcontrollers microprocessors stm32f3 series html img align left src readme assets book rtos valvano jpg width 8 height 8 the work is heavily inspired by the book real time operating systems for arm cortex m microcontrollers by jonathan w valvano https www amazon com embedded systems real time operating microcontrollers dp 1466468866 ref sr 1 1 which targets msp432 https www ti com tool msp exp432e401y and tm4c https www ti com tool ek tm4c123gxl microcontrollers from texas instruments like for the stm32f3 series those mcus are based on 32 bit arm cortex m4 https developer arm com processors cortex m4 processors br clear left to be more specific this rtos has been developed on the stm32f3discovery https www st com en evaluation tools stm32f3discovery html board so you may want to verify the peripherals and gpio pins used if you want to run it on a different board there are of course some differences between what s been presented in the book and what s been developed here first different boards feature different peripherals and different manifacturers provide different libraries to interface with them and second different coding styles led to different outcomes nonetheless if you pick up the book i m sure you can follow along quite easily last but not least if this readme taught you something new consider gifting it a star img src readme assets project jpg width 70 height 70 readme sections rtos features overview rtos features overview building and flashing building and flashing the rtos simply explained the rtos simply explained 0 what is an rtos 0 what is an rtos 1 initialize the mcu 1 initialize the mcu 2 initialize the linked list of tcbs 2 initialize the linked list of tcbs 3 initialize and start the periodic timer for the scheduler 3 initialize and start the periodic timer for the scheduler 4 start the first task 4 start the first task 5 perform the context switch when the periodic timer s interrupt triggers 5 perform the context switch when the periodic timers interrupt triggers bonus steps bonus steps 6 allow a task to suspend earlier 6 allow a task to suspend earlier 7 allow a task to sleep 7 allow a task to sleep inspecting the rtos with the logic analyzer inspecting the rtos with the logic analyzer added features on top of the barebone os added features on top of the barebone os features missing features missing discussion on reddit discussion on reddit diving into the project naming convention diving into the project naming convention diving into the project error handling diving into the project error handling diving into the project the instrumenttrigger macro diving into the project the instrumenttrigger macro diving into the project debugging hard faults diving into the project debugging hard faults rtos features overview as anticipated in the introduction this is a simple rtos that provides a limited number of features thread creation suspension sleeping and killing fixed stack size for each thread default to 400 bytes preemptive priority scheduling blocking semaphores as opposed to spin lock semaphores building and flashing the cmake setup follows the guidelines provided by this repository https github com majerle stm32 cube cmake vscode to run the software on your board first install all the required tools https github com majerle stm32 cube cmake vscode tools installation then clone the repo configure cmake build the executable and flash it to the board sh clone the repo git clone https github com dehre stm32f3 tiny rtos cd stm32f3 tiny rtos configure cmake cmake no warn unused cli dcmake export compile commands on dcmake build type debug dcmake toolchain file filepath cmake gcc arm none eabi cmake bbuild debug g ninja build cmake build build debug j 8 flash stm32 programmer cli connect port swd download build debug stm32f3 tiny rtos elf hardrst the rtos simply explained this readme section tries to explain how the rtos works before any bells and whistles are added to it if you want to follow along clone the repo and checkout it out at the barebone os tag https github com dehre stm32f3 tiny rtos commit 03e20f0cde2a6ea5b8408ee62aa3a604084b8c15 other features such as dynamic tasks creation and killing semaphores and better scheduling algorithms although not explained in detail here become much easier to figure out once the fundamentals are clear to ease the explanation further this section is broken down into 6 steps 0 what is an rtos 1 initialize the mcu 2 initialize the linked list of tcbs 3 initialize and start the periodic timer for the scheduler 4 start the first task 5 perform the context switch when the periodic timer s interrupt triggers 0 what is an rtos before going too far what is a real time operating system quoting https www highintegritysystems com rtos what is an rtos a real time operating system commonly known as an rtos is a software component that rapidly switches between tasks giving the impression that multiple programs are being executed at the same time on a single processing core in actual fact the processing core can only execute one program at any one time and what the rtos is actually doing is rapidly switching between individual programming threads or tasks to give the impression that multiple programs are executing simultaneously actually a fully fledged rtos offers many more features https docs zephyrproject org latest introduction index html distinguishing features but we keep it simple here so what is a task a task is a small piece of program which competes with other tasks to get the cpu resources it s just a regular function that runs continuously within an infinite loop and never returns core src user tasks c c void usertask 0 void while 1 do something remark the words task and thread are used interchangeably throughout the project even though their meaning isn t exactly the same generally a thread runs in a virtual address space https en wikipedia org wiki virtual address space whereas a task runs in a physical one given that this rtos like others https www freertos org freertos support forum archive november 2016 freertos free rtos memory management 59ed41adj html doesn t provide virtual address spaces it makes no difference here 1 initialize the mcu for the mcu to perform any work the nvic nested vectored interrupt controller the low level hardware and the system clock need to be initialized the fn hal init https github com stmicroelectronics stm32f3xx hal driver also initializes the systick periodic timer with period of 1 ms it will be used later for os sleep core src main c c int main void hal init systemclock config omitted 2 initialize the linked list of tcbs every task run by the rtos has a tcb a tcb thread control block is a struct encapsulating the state of the task core src os c c typedef struct tcb uint32 t sp stack pointer valid for threads not running struct tcb next pointer to circular linked list of tcbs tcb t a task is assigned its own stack and the sp field in the tcb points to the top of it stacks for the tasks are carved out of a static array named stacks and have a fixed size of 100 32 bit words 400 bytes the fn os addthreads first links together the tcb s in a circular list using the next field then it calls os setinitialstack which sets up the stack for each thread as if it had already been running and then suspended dummy values such as 0x07070707 are simply chosen to facilitate debugging finally it points the global variable runpt to an arbitrary tcb core src main c c int main void omitted os addthreads usertask 0 usertask 1 usertask 2 omitted core src os c c define numthreads 3 maximum number of threads define stacksize 100 number of 32 bit words in each tcb s stack static tcb t tcbs numthreads static uint32 t stacks numthreads stacksize pointer to the currently running thread tcb t runpt static void os setinitialstack uint32 t tcb idx from the stm32 cortex m4 programming manual on page 23 attempting to execute instructions when the t bit is 0 results in a fault or lockup stacks tcb idx stacksize 1 0x01000000 thumb bit psr stacks tcb idx stacksize 2 r15 pc set later in fn os addthreads stacks tcb idx stacksize 3 0x14141414 r14 lr stacks tcb idx stacksize 4 0x12121212 r12 stacks tcb idx stacksize 5 0x03030303 r3 stacks tcb idx stacksize 6 0x02020202 r2 stacks tcb idx stacksize 7 0x01010101 r1 stacks tcb idx stacksize 8 0x00000000 r0 stacks tcb idx stacksize 9 0x11111111 r11 stacks tcb idx stacksize 10 0x10101010 r10 stacks tcb idx stacksize 11 0x09090909 r9 stacks tcb idx stacksize 12 0x08080808 r8 stacks tcb idx stacksize 13 0x07070707 r7 stacks tcb idx stacksize 14 0x06060606 r6 stacks tcb idx stacksize 15 0x05050505 r5 stacks tcb idx stacksize 16 0x04040404 r4 tcbs tcb idx sp stacks tcb idx stacksize 16 thread s stack pointer void os addthreads void task0 void void task1 void void task2 void tcbs 0 next tcbs 1 tcbs 1 next tcbs 2 tcbs 2 next tcbs 0 os setinitialstack 0 stacks 0 stacksize 2 int32 t task0 pc os setinitialstack 1 stacks 1 stacksize 2 int32 t task1 pc os setinitialstack 2 stacks 2 stacksize 2 int32 t task2 pc thread 0 will run first runpt tcbs 0 3 initialize and start the periodic timer for the scheduler the fn os init initializes and starts the periodic schedltimer timer which triggers an interrupt when its count reaches zero the isr interrupt service routine will then be used by the os to regain control of the cpu and perform the context switch other details about the timer don t really matter core src main c c int main void omitted os init threadfreq os launch panic this statement should not be reached core src os c c void os init uint32 t scheduler frequency hz schedltimer init scheduler frequency hz void os launch void schedltimer start omitted 4 start the first task the fn osasm start is called it has to be written in assembly because cpu registers cannot be accessed from c core src os c c void os launch void omitted osasm start panic this statement should not be reached the function first dereferences runpt and gets the address of the thread s sp stack pointer which is placed first in the tcb struct then it pops the stack s values on the cpu registers core src os asm s s osasm start cpsid i disable interrupts ldr r0 runpt r0 runpt tcb t r0 runpt ldr r1 r0 r1 r0 tcb t r1 runpt ldr sp r1 sp r1 uint32 t sp runpt sp now we switched to the thread s stack which we populated before pop r4 r11 pop regs r4 r11 pop r0 r3 pop regs r0 r3 pop r12 pop reg r12 omitted finally it pops the first task s address to lr link register and jumps to it consequently the fn osasm start never returns from os start the fn usertask 0 starts running core src os asm s s osasm start omitted pop lr pop pc to the link register start location pop r1 discard psr cpsie i enable interrupts bx lr start first thread core src user tasks c c void usertask 0 void while 1 do something 5 perform the context switch when the periodic timer s interrupt triggers after usertask 0 has run for a while the periodic schedltimer counts to zero the interrupt triggers and the cpu jumps to the isr interrupt service routine who determines which function handles this interrupt it s determined by the vector table placed at memory address 0x0000 core startup startup stm32f303vctx s s the minimal vector table for a cortex m4 note that the proper constructs must be placed on this to ensure that it ends up at physical address 0x0000 0000 section isr vector a progbits type g pfnvectors object g pfnvectors word estack word reset handler word nmi handler word hardfault handler omitted word tim2 irqhandler omitted weak tim2 irqhandler thumb set tim2 irqhandler default handler the fn tim2 irqhandler defined as weak symbol in startup stm32f303vctx s is later overwritten in os asm s and is responsible for the context switch core src os asm s s for clarity the fn osasm threadswitch is exported as tim2 irqhandler so that the vector table in startup stm32f303vctx s doesn t need to be modified set tim2 irqhandler osasm threadswitch osasm threadswitch omitted first according to the aapcs https community arm com arm community blogs b architectures and processors blog posts on the aapcs with an application to efficient parameter passing arm architecture procedure call standard upon every function call the registers r0 r3 r12 lr pc psr are automatically saved on the stack remember the sp stack pointer is still pointing to the first thread s stack then the remaining registers r4 r11 are manually pushed to the stack and runpt sp updated with the latest sp stack pointer value core src os asm s s osasm threadswitch save r0 r3 r12 lr pc psr cpsid i prevent interrupt during context switch push r4 r11 save remaining regs r4 r11 ldr r0 runpt r0 runpt tcb t r0 runpt ldr r1 r0 r1 r0 tcb t r1 runpt str sp r1 r1 sp runpt sp sp omitted the first thread s context is now saved the interrupt flag is then cleared and runpt updated in a simple round robin fashion the fn os scheduler is written in c so that it becomes easier to update as the project grows finally as before the new runpt is dereferenced to get the address of the new thread s sp stack pointer the stack s values are popped to the cpu registers and the cpu returns from the interrupt before the function exits following the aapcs https community arm com arm community blogs b architectures and processors blog posts on the aapcs with an application to efficient parameter passing the pc program counter along with r0 r3 r12 lr psr are restored from the new thread s stack so the next task usertask 1 starts running core src os asm s s osasm threadswitch omitted push r0 lr push r0 and lr so that fn calls don t loose them bl schedltimer clearitflag clear schedltimer interrupt flag bl os scheduler call os scheduler runpt is updated pop r0 lr restore r0 and lr ldr r1 r0 r1 r0 tcb t r1 runpt ldr sp r1 sp r1 uint32 t sp runpt sp now we switched to the new thread s stack pop r4 r11 restore regs r4 r11 cpsie i tasks run with interrupts enabled bx lr restore r0 r3 r12 lr pc psr core src os c c void os scheduler void runpt runpt next core src user tasks c c void usertask 1 void while 1 do something now the rtos will keep switching between user tasks each time the periodic schedltimer counts to zero bonus steps with the core concepts understood adding simple features on top of the rtos becomes quite straightforward 6 allow a task to suspend earlier a task can decide to suspend before the end of its scheduled time slice and grant the cpu to the next task core src user tasks c c void usertask 1 void while 1 for uint32 t i 0 i 12 i do something os suspend the fn os suspend only needs to set the periodic schedltimer s counter to zero which in turn triggers the interrupt calls the isr and switches to the next thread back to step 5 core src os c c void os suspend void schedltimer resetcounter 7 allow a task to sleep a task can decide to enter the sleep state for an arbitrary amount of milliseconds core src user tasks c c void usertask 2 void uint32 t count 0 while 1 count if count 35 0 os sleep 4500 this information needs to be recorded in the tcb struct the thread will be sleeping if sleep is greater than zero core src os c c typedef struct tcb uint32 t sp stack pointer valid for threads not running struct tcb next pointer to circular linked list of tcbs uint32 t sleep sleep duration in ms zero means not sleeping tcb t to start sleeping the fn os sleep first sets the desired sleep value then suspends the task core src os c c void os sleep uint32 t sleep duration ms runpt sleep sleep duration ms os suspend the systick timer which was initialized by hal init back at step 1 is responsible for decrementing sleep every millisecond in all tcb s core src stm32f3xx it c c void systick handler void omitted os decrementtcbssleepduration core src os c c void os decrementtcbssleepduration void for size t tcb idx 0 tcb idx numthreads tcb idx if tcbs tcb idx sleep 0 tcbs tcb idx sleep 1 finally the scheduler is updated to skip all sleeping threads core src os c c void os scheduler void runpt runpt next while runpt sleep 0 runpt runpt next sleeping will not be precise the thread may sleep up to sleep time ms number running threads max preempt time ms depending on how many threads are scheduled to run before the awaked thread is run again inspecting the rtos with the logic analyzer let s now inspect how the barebone os https github com dehre stm32f3 tiny rtos commit 03e20f0cde2a6ea5b8408ee62aa3a604084b8c15 behaves using the logic analyzer the pins are connected as shown scheduler pb0 ch0 usertask 0 pe11 ch2 usertask 1 pe12 ch3 usertask 2 pe13 ch4 gnd gnd stm32f3discovery logic analyzer the pin pb0 is toggled each time the scheduler is invoked the other three pins are toggled by the user tasks in short usertask 0 just toggles pe11 every 60ms for its entire time slice usertask 1 toggles pe12 twelve times then suspends usertask 2 toggles pe13 thirty five times then sleeps for 4500ms core src user tasks c c void usertask 0 void instrumenttriggerpe11 init while 1 instrumenttriggerpe11 toggle hal delay 60 void usertask 1 void instrumenttriggerpe12 init while 1 for uint32 t i 0 i 12 i instrumenttriggerpe12 toggle hal delay 50 os suspend void usertask 2 void instrumenttriggerpe13 init uint32 t count 0 while 1 instrumenttriggerpe13 toggle count if count 35 0 os sleep 4500 else hal delay 70 here s the result readme assets screenshot logic analyzer png 0 the scheduler is called usertask 0 starts running 1 after 1 second schedltimer counts to zero a context switch happens and usertask 1 starts running 2 usertask 1 suspends before the end of its time slice usertask 2 starts running 3 usertask 2 runs until the end of its time slice because it hasn t counted to 35 yet then usertask 0 starts running again 4 after 1 second schedltimer counts to zero a context switch happens and usertask 1 starts running 5 usertask 1 suspends before the end of its time slice usertask 2 starts running 6 usertask 2 counts to 35 and starts sleeping for 4500ms then usertask 0 starts running 7 usertask 2 wakes up after more than 4500ms and starts counting again from 0 remark if you want to inspect the logic analyzer session yourself install logic2 from saleae https www saleae com downloads and open the file readme assets saleae logic2 session sal https github com dehre stm32f3 tiny rtos blob main readme assets saleae logic2 session sal added features on top of the barebone os more features have been added on top of the barebone os https github com dehre stm32f3 tiny rtos commit 03e20f0cde2a6ea5b8408ee62aa3a604084b8c15 described above dynamic thread creation https github com dehre stm32f3 tiny rtos blob main core src os c l220 and killing https github com dehre stm32f3 tiny rtos blob main core src os c l307 in short any thread can spawn a new thread at runtime and or kill itself as before the stack size is fixed to 400 bytes to avoid any dynamic memory allocation the maximum number of threads that can be created is defined at compile time semaphores https github com dehre stm32f3 tiny rtos blob main core src os c l329 threads can block waiting on a semaphore and they won t be picked by the scheduler to run until that semaphore is signaled the project includes a multi consumer multi producer fifo queue https github com dehre stm32f3 tiny rtos blob main core src fifo queue c built on top of the os semaphore as well as an example of switch debounce https github com dehre stm32f3 tiny rtos blob main core src onboard user button c the onboard switch priority scheduling https github com dehre stm32f3 tiny rtos blob main core src os c l262 upon creation the user can assign each task a fixed priority from 0 highest to 255 lowest the rules for the scheduler are simple if priority task a priority task b task a runs if priority task b priority task a task b runs if priority task a priority task b task a and task b are run in round robin fashion features missing of course plenty of features are missing perhaps the most relevant are memory protection https www freertos org freertos mpu memory protection unit html stack overflow protection if a task allocates on the stack more than the predefined number of bytes 400 by default the os will happily start overwriting another thread s stack or throw a segmentation fault priority inheritance https en wikipedia org wiki priority inheritance an high priority task could starve waiting for a semaphore to be signaled from a low priority one aging https en wikipedia org wiki aging scheduling low priority tasks may never be scheduled to run address space virtualization https en wikipedia org wiki virtual address space like most other rtoses tasks don t have their own address space quoting from this post https www freertos org freertos support forum archive november 2016 freertos free rtos memory management 59ed41adj html as far as i know no freertos does not deal with virtual spaces memory in part because virtual memory is the enemy of real time the linux real time extensions as far as i know just lock the real time parts into memory the problem is that paging in virtual memory adds significant unpredictability to timing discussion on reddit this project received a lot of relevant and well written feedback on reddit https www reddit com r embedded comments voxdj4 a tiny rtos simply explained which adds great value to this readme if you ve read this far consider checking it out too diving into the project naming convention as this rtos uses the stm32 hal driver https github com stmicroelectronics stm32f3xx hal driver all code sticks to its naming convention to avoid a weird reading experience in short c global function and variable void mymodule globalfn void uint32 t mymodule globalvar static function and variable internal linkage static void staticfn void static uint32 t staticvar local function and variable void local fn ptr void uint32 t local var diving into the project error handling to enhance readability and simplify development the rtos panics as soon as an error occurs instead of bubbling it up the fn panic in turn calls the bkpt instruction https developer arm com documentation dui0473 m arm and thumb instructions bkpt so that pinpointing and fixing bugs becomes as quick as possible the macros assert or panic and iferr panic https github com dehre stm32f3 tiny rtos blob main core inc iferr h helped with the chore c void panic void disable irq asm bkpt 1 define assert or panic expr expr void 0u panic define iferr panic x do hal statustypedef err x if err hal ok panic while 0 usage c assert or panic arg 0 iferr panic some fn arg diving into the project the instrumenttrigger macro a debugging heartbeat is a nice and minimally intrusive tool for profiling embedded software with an oscilloscope or logic analyzer it s used multiple time across this codebase to reduce boilerplate code the module instrument trigger https github com dehre stm32f3 tiny rtos blob main core inc instrument trigger h provides the macro instrumenttrigger create which generates functions to initialize a gpio pin as push pull output and toggle it usage c include instrument trigger h instrumenttrigger create e 13 now these functions are available void instrumenttriggerpe13 init void void instrumenttriggerpe13 set void void instrumenttriggerpe13 reset void void instrumenttriggerpe13 toggle void void instrumenttriggerpe13 read void int some fn void instrumenttriggerpe13 init while 1 instrumenttriggerpe13 toggle hal delay 1000 diving into the project debugging hard faults hard faults happened multiple times when developing this project especially when messing up with assembly no compile errors whatsoever and the program just enters an infinite loop this article has been very useful in such incidents how to debug a hardfault on an arm cortex m mcu interrupt https interrupt memfault com blog cortex m fault debug to speed up detecting which specific fault took place the hardfault handler reads the configurable fault status registers cfsr and the hardfault status register hfsr and parses their bits into the struct below then it s just matter of inspecting the hardfaultstatusregs variable with gdb core src stm32f3xx it c c typedef struct uint32 t cfsreg configurable fault status register uint16 t ufsreg usage fault status registers uint8 t bfsreg bus fault status registers uint8 t mmfsreg memory manage fault status registers uint32 t hfsreg hardfault status register usage faults bool divbyzero bool unaligned bool nocp bool invpc bool invstate bool undefinstr bus faults bool bfarvalid bool lsperr bool stkerr bool unstkerr bool impreciserr bool preciserr bool ibuserr memmanage faults bool mmarvalid bool mlsperr bool mstkerr bool munstkerr bool daccviol bool iaccviol hard faults bool debugevt bool forced bool vecttbl hardfaultstatusregisters t static used hardfaultstatusregisters t hardfaultstatusregs | c rtos stm32f3-discovery cmake | os |
raven-llms | raven llms large language models requirement linux os python version 3 10 setup create virtual environment activate virtual environment | ai |
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atomize | p align center a href http atomizecode com img width 110px style margin right 20px src https firebasestorage googleapis com v0 b pawan dev appspot com o logo svg alt media a p h1 align center atomize code h1 div align center ui design system for react js npm package https img shields io npm v atomize svg style flat square https www npmjs org package atomize npm downloads http img shields io npm dm atomize svg style flat square http npmjs com atomize prs welcome https img shields io badge prs welcome brightgreen svg style flat square http makeapullrequest com div https firebasestorage googleapis com v0 b pawan dev appspot com o screenshot 202019 07 19 20at 2011 16 03 20am png alt media http atomizecode com features ui design system for web apps elegant and beautiful react components environment support modern browsers and internet explorer 9 server side rendering electron http electron atom io img src https raw githubusercontent com alrra browser logos master src edge edge 48x48 png alt ie edge width 24px height 24px http godban github io browsers support badges br ie edge img src https raw githubusercontent com alrra browser logos master src firefox firefox 48x48 png alt firefox width 24px height 24px http godban github io browsers support badges br firefox img src https raw githubusercontent com alrra browser logos master src chrome chrome 48x48 png alt chrome width 24px height 24px http godban github io browsers support badges br chrome img src https raw githubusercontent com alrra browser logos master src safari safari 48x48 png alt safari width 24px height 24px http godban github io browsers support badges br safari img src https raw githubusercontent com alrra browser logos master src opera opera 48x48 png alt opera width 24px height 24px http godban github io browsers support badges br opera img src https raw githubusercontent com alrra browser logos master src electron electron 48x48 png alt electron width 24px height 24px http godban github io browsers support badges br electron ie9 ie10 ie11 edge last 2 versions last 2 versions last 2 versions last 2 versions last 2 versions install bash npm install atomize react transition group bash yarn add atomize react transition group usage jsx import button from atomize reactdom render button mountnode links home page http atomizecode com getting started https atomizecode com docs react setup showcase https atomizecode com docs react showcase contributing https atomizecode com docs react contributing theme setup https atomizecode com docs react theme atoms https atomizecode com docs react atoms molecules https atomizecode com docs react molecules functions https atomizecode com docs react functions examples search box https codesandbox io s search box 0fc6c star rating https codesandbox io s star rating 64ex1 login form https codesandbox io s login form atomize ezs4u payment card https codesandbox io s payment card 42b3c pokedex https warpokex ri7nz now sh repository https github com ri7nz warpokex development to clone locally bash git clone git github com proksh atomize git cd atomize npm install or yarn npm start open your browser and visit http localhost 8080 contributing prs welcome https img shields io badge prs welcome brightgreen svg style flat square http makeapullrequest com read our contributing guide https atomizecode com docs react contributing and let s build a better atomize together | design-system reactjs ui ui-framework design | os |
NSBMEZ_FrontEnd | nsbmez license https img shields io badge license mit blue svg https github com your nsbmez blob main license github contributors https img shields io github contributors your nsbmez svg https github com your nsbmez graphs contributors description nsbmez is a mobile application developed for nsbm green university with the aim of enhancing the overall experience for students lecturers and faculty members this project focuses on providing various functionalities to streamline daily activities within the university the key features of the application include transport service timetable and bus availability this feature allows users to access the timetable for the university s transport services and check bus availability in real time lecture timetable and notification system the application provides an organized lecture timetable and a notification system to keep users updated about their class schedules and any changes or announcements online payment method nsbmez offers a convenient online payment method allowing users to make secure payments for various services and facilities provided by the university result view and gpa calculation students can view their academic results within the application and calculate their gpa grade point average based on the grades obtained event allocation time table the application also includes an event allocation time table which helps users stay informed about upcoming university events and their allocated schedules the front end design of nsbmez is developed using flutter a popular framework for building cross platform applications the use of flutter ensures a visually appealing and responsive user interface across both android and ios platforms for the back end the application utilizes firebase a powerful and scalable cloud based platform provided by google firebase offers seamless data storage real time database synchronization and user authentication making it an ideal choice for managing the application s back end functionalities to enhance the user experience nsbmez integrates apis for tracking maps and live location services this feature enables users to track their routes find locations within the university and access real time information about their current position contributors this project is the collective effort of the following contributors m a sriyanjith https github com contributor1 w a t lankathilaka https github com contributor2 r m m deshpriya https github com contributor3 e v p dulakshitha https github com contributor3 d k jayalal https github com contributor3 k p h t pathirana https github com contributor3 we appreciate the time and expertise contributed by these individuals which has helped shape nsbmez into a comprehensive and user friendly mobile application license nsbmez is licensed under the mit license https github com madushan13 nsbmez blob main license feel free to modify and distribute the code subject to the terms and conditions of this license technical stack flutter https img shields io badge frontend flutter blue logo flutter logocolor white firebase https img shields io badge backend firebase orange logo firebase logocolor white api https img shields io badge map 20 26 20location 20apis integration green logo google maps logocolor white installation to install and run nsbmez on your device follow these steps 1 clone the repository bash git clone https github com your nsbmez git 2 install the necessary dependencies bash cd nsbmez flutter pub get 3 build and run the application bash flutter run make sure you have flutter sdk installed and properly configured in your development environment before proceeding with the installation for detailed instructions on setting up flutter refer to the official flutter documentation getting started with flutter https flutter dev docs get started feedback and contributions we welcome any feedback or suggestions for improving nsbmez if you encounter any issues or would like to contribute to the project please feel free to submit a pull request or open an issue on github let s make nsbmez a valuable resource for the nsbm green university | front_end |
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mvcvm-swift-file-templates | ios swift file templates for xcode using img src assets rx logo m png alt feel the power of rxswift width 24 height 24 rxswift rxcocoa and rxdatasources about this project these templates are designed to speed up and make the ios development so much easier by eliminating the repeating processes and making your code better organized dependencies the templates are using some reactive libraries such as rxswift https github com reactivex rxswift rxcocoa https github com reactivex rxswift tree master rxcocoa and rxdatasources https github com rxswiftcommunity rxdatasources usage installing to install the templates run the install templates sh script in the terminal shell install templates sh uninstalling if you d like to remove the previously installed templates run the uninstall templates sh script shell uninstall templates sh updating for updating the templates you must remove them first then run the install script shell uninstall templates sh install templates sh preparing your project add these pods to your xcode project ruby pod rxswift 4 1 1 pod rxcocoa 4 1 1 pod rxdatasources 3 0 2 you also have to add the files from tableview requirements template just press kbd cmd kbd kbd n kbd or right click on your source files in xcode and select new file scoll down to mv c vm utilities section and select tableview requirements then click on next and create now you re done and you can use all the templates img src assets tutorial 1 gif alt adding the tableview requirements with these easy steps you can make a list presenting some data step 1 add a cell with model from the previously installed templates add the necessary properties to your model add an init method to the model and pass these properties as parameters step 2 add properties variable types to the viewmodel which going to be connected with the cell s outlets in the viewmodel there ll be a variable var model with the same type of the model this variable will have a didset method update the viewmodel properties here step 3 create the outlets in the cell not required in this example bind the cell s outlets with the viewmodel s properties in the setupbindings method step 4 add a tableview ih with multi sections from the previously installed templates fill the viewcontroller s viewmodel with some data sections property step 5 add a uitableviewcontroller to the storyboard and set its class set the entry point add a prototype cell to the tableview and set its class and the reuseidentifier also add the necassary outlets and constraints to the cell not required in this example connect these outlets with the code not required in this example final step build and run video tutorial https youtu be lrhbwwcux3y examples simple example https github com egabor swift mvcvm tableview example 2 detailed example coming soon donations all donations are appreciated btc address 127tuy5nwp3ucv6uweion1ccgeraexsfzv eth address 0x53510eb7e2c683e28ecefefc0b0a887227ed3da6 don t forget to leave a star here meaning of emojis used in commit messages commit type emoji initial commit party popper metadata bookmark new feature sparkles bugfix bug version tag admission tickets refactoring black universal recycling symbol documentation books internationalization globe with meridians performance horse cosmetic artist palette tooling wrench tests police cars revolving light deprecation pile of poo removal wastebasket work in progress wip construction sign lint shirt shirt translation alien alien critical hotfix ambulance ambulance accessibility wheelchair wheelchair code review changes ok hand ok hand analytics or tracking code chart with upwards trend chart with upwards trend removing a dependency heavy minus sign heavy minus sign adding a dependency heavy plus sign heavy plus sign security lock lock general update zap zap text pencil pencil | ios swift xcode xctemplate templates tableview mvvm mvcvm reactive rxswift | front_end |
CrossFront-Simple | crossfront cross platform front end glue crossfront uses these frameworks typescript backbone underscore require jquery jquery mobile jquery mobile router cordova phonegap modernizr crossfront glues all these frameworks together in a boilerplate project to allow for large scale javascript development it allows you to code once and run everywhere desktop browsers mobile browsers tablet browsers phones android ios etc crossfront is a great front end solution for app development that provides good structure and organzation of code using amd and mvc design patterns it the ideal compliment to a restful backend here are the steps to get this project working 1 download visual studio 2012 i downloaded the premium release version not sure if these instruction will work with express rc or beta let me know if it does 2 install the visual studio add in for typescript here http www microsoft com en us download details aspx id 34790 3 if your using git then clone my project git clone https github com ntheile crossfront simple git 4 note i had to turn off vs2012 from compiling my code because i needed to to compile as adm to do this right click the ts file goto properties build action change to none 5 now compile each manually using the commands in compile notes txt example tsc app ts module amd 6 hint run the commands from the package manager console in visual studio to avoid having to switch out to a dos prompt | server |
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projects | projects this repository is for projects related to the missoula college information technology program | server |
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flow | flow https www flow com flow is a fast secure and developer friendly blockchain built to support the next generation of games apps and the digital assets that power them for a high level overview of flow s architecture check out the primer https www flow com primer details about the protocol can be found in the technical papers https www flow com technical paper for more documentation and tutorials check out developer portal https developers flow com find out more about flow improvement proposals flips in flow flips https github com onflow flips | blockchain smart-contracts onflow | blockchain |
Email-Classifier | email classification this is a text classification project which is a multi class classification various classifiers are trained and tested using python it includes the classification of emails based on their content into three categories normal spam and fraud various classifiers including support vector machine svm k nearest neighbour multinomial na ve bayes decision tree logistic regression svm with stochastic gradient descent classifier sgd svm and logistic regression with stochastic gradient descent classifier sgd lr are trained on features extracted using tf idf vectorizer further ensemble classifiers including random forest rf adaboost bagging bgc extra trees and vote on various classifier combinations are trained in a similar manner also the effect of stemming on the model performance is observed additionally classifiers are trained on the features extracted using count vectorizer finally all the models are evaluated based on standard evaluation metrics accuracy precision recall f score and confusion matrix it is observed that vote on svm bgc and rf outperform all the models followed by sgd svm trained on tf idf features without stemming prerequisites ul li python 3 x li li libraries li ul li pandas li li sklearn li li nltk li li numpy li li matplotlib li li string li li re li li random li ul ul code brief the entire coding is done in python3 5 which was executed in spyder which is a part of anaconda3 there are two python files extract email py and email classification py which involves the process of data extraction and text processing and classification respectively i extract email py this file involves the process of data extraction in this 1000 fraud emails from the fradulent emails txt file containing 4075 emails are extracted and 1000 emails for each spam and normal category are extracted from emails csv file that contains 5730 emails which is a combination of both spam and normal emails finally all the extracted emails are concatenated into one csv file this csv file contains the final dataset that contains 3000 emails with 1000 emails for each category note for the proper execution of the code update the paths for ul li the final csv file to be created final dataset csv li li fradulent emails txt file file containing fraud emails li li emails csv file file containing spam and normal emails li ul ii email classification py this file involves the complete process of email processing and classification 1 data preprocessing functions are created for the removal of punctuation and stopwords another function is created for stemming of the content in order to extract the relevant features 2 vectors were used tf idf vectors and count vectors first the entire process of classification is performed by the features created using tf idf and then the features created by count vectorizer are processed and observed then the features are split into train and test set in the ratio 7 3 respectively 2 text classification various classifers are trained on the features extracted above and then their performance is observed before the training of the models parameter tuning is performed to identify the optimum parameters for each classifier 3 evaluation metrics the classifiers are evaluated on the basis of ul li accuracy li li confusion matrix li li precision recall and f score li ul note for the execution of the code change the path for final dataset csv that was created in the previous step for the variable input dataset | ai |
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Hsopital-Information-Management-System-SWE-Lab- | hsopital information management system swe lab project based on front end as well as backend development in the frontend part html css and javascript used and in the backend part mysql software used vscode and xampp server it is a app like thing we have to start using xampp server | server |
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clojure-xamarin | clojure xamarin this is an effort to get clojureclr https github com clojure clojure clr working with xamarin http xamarin com for cross platform native mobile app development | front_end |
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L3MVN | l3mvn leveraging large language models for visual target navigation this work is based on our paper we proposed a new framework to explore and search for the target in unknown environment based on large language model our work is based on semexp https github com devendrachaplot object goal navigation and llm scene understanding https github com neurips2020submission invalid action masking implemented in pytorch author bangguo yu hamidreza kasaei and ming cao affiliation university of groningen frontier semantic exploration framework visual target navigation in unknown environments is a crucial problem in robotics despite extensive investigation of classical and learning based approaches in the past robots lack common sense knowledge about household objects and layouts prior state of the art approaches to this task rely on learning the priors during the training and typically require significant expensive resources and time for learning to address this we propose a new framework for visual target navigation that leverages large language models llm to impart common sense for object searching specifically we introduce two paradigms i zero shot and ii feed forward approaches that use language to find the relevant frontier from the semantic map as a long term goal and explore the environment efficiently our analysis demonstrates the notable zero shot generalization and transfer capabilities from the use of language experiments on gibson and habitat matterport 3d hm3d demonstrate that the proposed framework significantly outperforms existing map based methods in terms of success rate and generalization ablation analysis also indicates that the common sense knowledge from the language model leads to more efficient semantic exploration finally we provide a real robot experiment to verify the applicability of our framework in real world scenarios the supplementary video and code can be accessed via the following link https sites google com view l3mvn image 20200706200822807 img system png requirements ubuntu 20 04 python 3 7 habitat lab https github com facebookresearch habitat lab installation the code has been tested only with python 3 7 cuda 10 nvcc on ubuntu 20 04 1 installing dependencies we use challenge 2022 versions of habitat sim https github com facebookresearch habitat sim and habitat lab https github com facebookresearch habitat lab as specified below installing habitat sim git clone https github com facebookresearch habitat sim git cd habitat sim git checkout tags challenge 2022 pip install r requirements txt python setup py install headless python setup py install for mac os installing habitat lab git clone https github com facebookresearch habitat lab git cd habitat lab git checkout tags challenge 2022 pip install e install pytorch https pytorch org according to your system configuration the code is tested on pytorch v1 6 0 and cudatoolkit v10 2 if you are using conda conda install pytorch 1 6 0 torchvision 0 7 0 cudatoolkit 10 2 linux with gpu conda install pytorch 1 6 0 torchvision 0 7 0 c pytorch mac os install detectron2 https github com facebookresearch detectron2 according to your system configuration if you are using conda python m pip install detectron2 f https dl fbaipublicfiles com detectron2 wheels cu102 torch1 6 index html linux with gpu cc clang cxx clang archflags arch x86 64 python m pip install git https github com facebookresearch detectron2 git mac os 2 download hm3d datasets habitat matterport download hm3d https aihabitat org datasets hm3d dataset using download utility and instructions https github com facebookresearch habitat sim blob 089f6a41474f5470ca10222197c23693eef3a001 datasets hm3d md python m habitat sim utils datasets download username api token id password api token secret uids hm3d minival 3 download additional datasets download the segmentation model https drive google com file d 1u0ds44dipz22ntjw0rfo431zv lmpcvv view usp share link in rednet model path setup clone the repository and install other requirements git clone https github com ybgdgh l3mvn cd l3mvn pip install r requirements txt setting up datasets the code requires the datasets in a data folder in the following format same as habitat lab object goal navigation data scene datasets matterport category mappings tsv object norm inv perplexity npy versioned data objectgoal hm3d train val val mini for evaluation for evaluating the pre trained model python main llm vis py split val eval 1 auto gpu config 0 n 1 num eval episodes 2000 load pretrained models llm model pt use gtsem 0 num local steps 10 demo video video https sites google com view l3mvn | ai |
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davidensinger.github.io | davidensinger github io david ensinger is a front end developer from columbus oh this website runs on jekyll http jekyllrb com a blog aware static site generator with a lot of help from grunt http gruntjs com the stack bower http bower io manage front end dependencies bundler http gembundler com manage ruby dependencies graphicsmagick http sourceforge net projects graphicsmagick required for grunt responsive images https github com andismith grunt responsive images grunt http gruntjs com automate jekyll development and build tasks node js http nodejs org and npm https npmjs org required for grunt ruby http www ruby lang org required for jekyll recommended setup ensure that command line tools for xcode https developer apple com xcode is installed and up to date to install xcode select install manage your ruby enviroments with rvm https rvm io or rbenv https github com sstephenson rbenv to update rvm rvm get stable make sure your installs of node js http nodejs org and npm https npmjs org are up to date install the command line interface for grunt http gruntjs com to install npm install g grunt cli install bower http bower io to install npm install g bower make sure you ve installed graphicsmagic presumably via homebrew to install brew install graphicsmagick install dependencies run the following commands to install the dependencies bower bower install bundler bundle install npm npm cache clean and then npm install grunt workflow grunt stage copies the loadfont and loadcss functions from bower to the jekyll includes directory grunt serve compiles all files and opens the site in your default browser a watch task watches for changes to files recompiles if necessary and injects the changes into the browser with browsersync grunt check checks for outdated dependencies with grunt dev update javascript code quality with jshint sass code quality with scss lint https github com causes scss lint and jekyll health with jekyll doctor grunt build builds an optimized site to the dist directory grunt deploy runs the perf task runs the build task and then deploys it grunt perf checks google s pagespeed insights and then runs phantomas https github com macbre phantomas to return and record site metrics hat tip the site was scaffolded by yeoman http yeoman io and generator jekyllrb https github com robwierzbowski generator jekyllrb | personal-website | front_end |
MyFirstGitProject | myfirstgitproject my first git project for learning towards cloud and software engineering | cloud |
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awesome-zephyr | awesome zephyr rtos awesome https awesome re badge svg https awesome re img src https raw githubusercontent com fkromer awesome zephyr master logo svg sanitize true align right width 86 https www zephyrproject org a curated list of awesome zephyr rtos zephyr project https www zephyrproject org resoures contents zephyr core components zephyr core components guides guides best practices best practices suggested uses suggested uses api reference api reference zephyr modules zephyr modules virtualization virtualization hardware abstraction hardware abstraction releases releases vscode extensions vscode extensions development containers development containers development frameworks development frameworks blog posts blog posts videos videos zephyr core components zephyr https github com zephyrproject rtos zephyr zephyr rtos west https github com zephyrproject rtos west meta tool cmake https cmake org build system make https www gnu org software make build tool option 1 ninja https ninja build org build tool option 2 kconfig https www kernel org doc html latest kbuild kconfig language html build configuration devicetree https www devicetree org hardware description guides zephyr v2 6 99 getting started guide https docs zephyrproject org latest getting started index html beyond the getting started guide https docs zephyrproject org latest guides beyond gsg html user and developer guides https docs zephyrproject org latest guides index html secure coding https docs zephyrproject org latest security secure coding html board porting guide https docs zephyrproject org latest guides porting board porting html devicetree guide https docs zephyrproject org latest guides dts index html architecture porting guide https docs zephyrproject org latest guides porting arch html architecture related guides https docs zephyrproject org latest guides arch index html contribution guidelines https docs zephyrproject org latest contribute index html best practices zephyr v2 6 99 kconfig tips and best practices https docs zephyrproject org latest guides build kconfig tips html suggested uses zephyr v2 6 99 kernel services scheduling interrupts and synchronization threads https docs zephyrproject org latest reference kernel threads index html suggested uses scheduling https docs zephyrproject org latest reference kernel scheduling index html suggested uses system threads https docs zephyrproject org latest reference kernel threads system threads html suggested uses workqueue threads https docs zephyrproject org latest reference kernel threads workqueue html suggested uses zephyr without threads https docs zephyrproject org latest reference kernel threads nothread html interrupts https docs zephyrproject org latest reference kernel other interrupts html suggested uses polling api https docs zephyrproject org latest reference kernel other polling html suggested uses semaphores https docs zephyrproject org latest reference kernel synchronization semaphores html suggested uses mutexes https docs zephyrproject org latest reference kernel synchronization mutexes html suggested uses condition variables https docs zephyrproject org latest reference kernel synchronization condvar html suggested uses symmetric multiprocesssing https docs zephyrproject org latest reference kernel smp smp html data passing fifos https docs zephyrproject org latest reference kernel data passing fifos html suggested uses lifos https docs zephyrproject org latest reference kernel data passing lifos html suggested uses stacks https docs zephyrproject org latest reference kernel data passing stacks html suggested uses message queue https docs zephyrproject org latest reference kernel data passing message queues html suggested uses mailboxes https docs zephyrproject org latest reference kernel data passing mailboxes html suggested uses pipes https docs zephyrproject org latest reference kernel data passing pipes html suggested uses memory management memory heaps https docs zephyrproject org latest reference kernel memory heap html suggested uses memory slabs https docs zephyrproject org latest reference kernel memory slabs html suggested uses timing timers https docs zephyrproject org latest reference kernel timing timers html suggested uses other cpu idling https docs zephyrproject org latest reference kernel other cpu idle html highlight suggested 20uses suggested uses atomic services https docs zephyrproject org latest reference kernel other atomic html highlight suggested 20uses suggested uses floating point services https docs zephyrproject org latest reference kernel other float html suggested uses c support for applications https docs zephyrproject org latest reference kernel other cxx support html api reference zephyr v2 6 99 api status https docs zephyrproject org latest reference api index html audio codec https docs zephyrproject org latest reference audio codec html the audio codec api provides access to digital audio codecs dmic https docs zephyrproject org latest reference audio dmic html the audio dmic interface provides access to digital microphones i2s https docs zephyrproject org latest reference audio i2s html the i2s inter ic sound api provides support for the standard i2s interface as well as common non standard extensions such as pcm short long frame sync and left right justified data formats asynchronous notification https docs zephyrproject org latest reference misc notify html bluetooth https docs zephyrproject org latest reference bluetooth index html crypto https docs zephyrproject org latest reference crypto index html crypto hardware related functionalities devicetree https docs zephyrproject org latest reference devicetree index html device driver model https docs zephyrproject org latest reference drivers index html display interface https docs zephyrproject org latest reference display index html error detection and correction edac https docs zephyrproject org latest reference edac index html file systems https docs zephyrproject org latest reference file system index html formatted output https docs zephyrproject org latest reference misc formatted output html kernel services scheduling interrupts and synchronization threads https docs zephyrproject org latest reference kernel threads index html api reference workqueue threads https docs zephyrproject org latest reference kernel threads workqueue html api reference interrupts https docs zephyrproject org latest reference kernel other interrupts html api reference polling https docs zephyrproject org latest reference kernel other polling html api reference semaphores https docs zephyrproject org latest reference kernel synchronization semaphores html api reference user mode semaphores https docs zephyrproject org latest reference kernel synchronization semaphores html user mode semaphore api reference mutexes https docs zephyrproject org latest reference kernel synchronization mutexes html api reference futex mutexes https docs zephyrproject org latest reference kernel synchronization mutexes html futex api reference user mode mutexes https docs zephyrproject org latest reference kernel synchronization mutexes html user mode mutex api reference condition variables https docs zephyrproject org latest reference kernel synchronization condvar html api reference data passing queues https docs zephyrproject org latest reference kernel data passing queues html api reference fifos https docs zephyrproject org latest reference kernel data passing fifos html api reference lifos https docs zephyrproject org latest reference kernel data passing lifos html api reference stacks https docs zephyrproject org latest reference kernel data passing stacks html api reference message queues https docs zephyrproject org latest reference kernel data passing message queues html api reference mailboxes https docs zephyrproject org latest reference kernel data passing mailboxes html api reference pipes https docs zephyrproject org latest reference kernel data passing pipes html api reference memory management memory heap https docs zephyrproject org latest reference kernel memory heap html api reference memory slabs https docs zephyrproject org latest reference kernel memory slabs html api reference timing kernel timing https docs zephyrproject org latest reference kernel timing clocks html api reference timers https docs zephyrproject org latest reference kernel timing timers html api reference other cpu idling https docs zephyrproject org latest reference kernel other cpu idle html api reference atomic services https docs zephyrproject org latest reference kernel other atomic html api reference floating point services https docs zephyrproject org latest reference kernel other float html api reference version https docs zephyrproject org latest reference kernel other version html api reference fatal errors https docs zephyrproject org latest reference kernel other fatal html api reference c standard library https docs zephyrproject org latest reference libc index html minimal newlib logging https docs zephyrproject org latest reference logging index html memory management demand paging https docs zephyrproject org latest reference memory management demand paging html miscellaneous checksum crc https docs zephyrproject org latest reference misc index html crc structured data json https docs zephyrproject org latest reference misc index html json jwt https docs zephyrproject org latest reference misc index html jwt data structures single linked list single linked list https docs zephyrproject org latest reference data structures slist html single linked list api reference flagged list https docs zephyrproject org latest reference data structures slist html flagged list api reference doubly linked list https docs zephyrproject org latest reference data structures dlist html doubly linked list api reference multi producer single consumer packet buffer https docs zephyrproject org latest reference data structures mpsc pbuf html usage balanced red black tree https docs zephyrproject org latest reference data structures rbtree html red black tree api reference ring buffers https docs zephyrproject org latest reference data structures ring buffers html api reference modbus https docs zephyrproject org latest reference modbus index html peripherals adc https docs zephyrproject org latest reference peripherals adc html api reference counter https docs zephyrproject org latest reference peripherals counter html api reference clock control https docs zephyrproject org latest reference peripherals clock control html api reference dac https docs zephyrproject org latest reference peripherals dac html api reference dma https docs zephyrproject org latest reference peripherals dma html api reference ec host command https docs zephyrproject org latest reference peripherals ec host cmd periph html api reference eeprom https docs zephyrproject org latest reference peripherals eeprom html api reference entropy https docs zephyrproject org latest reference peripherals entropy html api reference flash user api https docs zephyrproject org latest reference peripherals flash html user api reference implementation interface api https docs zephyrproject org latest reference peripherals flash html implementation interface api reference gna https docs zephyrproject org latest reference peripherals gna html api reference gpio https docs zephyrproject org latest reference peripherals gpio html api reference hardware information https docs zephyrproject org latest reference peripherals hwinfo html api reference i2c eeprom slave https docs zephyrproject org latest reference peripherals i2c eeprom slave html api reference i2c https docs zephyrproject org latest reference peripherals i2c html api reference ipm https docs zephyrproject org latest reference peripherals ipm html api reference kscan https docs zephyrproject org latest reference peripherals kscan html api reference led https docs zephyrproject org latest reference peripherals led html api reference pinmux https docs zephyrproject org latest reference peripherals pinmux html api reference pwm https docs zephyrproject org latest reference peripherals pwm html api reference ps 2 https docs zephyrproject org latest reference peripherals ps2 html api reference peci https docs zephyrproject org latest reference peripherals peci html api reference regulators https docs zephyrproject org latest reference peripherals regulators html api reference rtc https docs zephyrproject org latest reference peripherals rtc html api reference sensors https docs zephyrproject org latest reference peripherals sensor html api reference spi https docs zephyrproject org latest reference peripherals spi html api reference uart https docs zephyrproject org latest reference peripherals uart html api reference watchdog https docs zephyrproject org latest reference peripherals watchdog html api reference video https docs zephyrproject org latest reference peripherals video html api reference espi https docs zephyrproject org latest reference peripherals espi html api reference power management power management hook interface https docs zephyrproject org latest reference power management index html power management hook interface system power management apis https docs zephyrproject org latest reference power management index html system power management apis device power management api https docs zephyrproject org latest reference power management index html device power management api the soc interface and application use these api to perform power management operations on the devices device runtime power management api https docs zephyrproject org latest reference power management index html device runtime power management api the device drivers use these api to perform device runtime power management operations on the devices random number generation https docs zephyrproject org latest reference random index html api reference resource management on off manager api https docs zephyrproject org latest reference resource management index html on off manager shell https docs zephyrproject org latest reference shell index html api reference storage non volatile storage nvs https docs zephyrproject org latest reference storage nvs nvs html api reference disk access https docs zephyrproject org latest reference storage disk access html api reference flash map https docs zephyrproject org latest reference storage flash map flash map html api reference flash circular buffer fcb https docs zephyrproject org latest reference storage fcb fcb html api reference stream flash https docs zephyrproject org latest reference storage stream stream flash html api reference task watchdog https docs zephyrproject org latest reference task wdt index html api reference time utilities representation transformation https docs zephyrproject org latest reference misc timeutil html representation transformation time scale synchronization https docs zephyrproject org latest reference misc timeutil html time scale synchronization usb device stack usb device controller https docs zephyrproject org latest reference usb index html usb device controller api usb device core https docs zephyrproject org latest reference usb index html usb device core layer api low level high level api hid class device https docs zephyrproject org latest reference usb index html hid class device api user mode memory domain https docs zephyrproject org latest reference usermode memory domain html api reference kernel object https docs zephyrproject org latest reference usermode kernelobjects html api reference system calls https docs zephyrproject org latest reference usermode syscalls html apis utilities https docs zephyrproject org latest reference util index html settings api for general settings usage https docs zephyrproject org latest reference settings index html api for general settings usage api for key name processing https docs zephyrproject org latest reference settings index html api for key name processing api for runtime settings manipulation https docs zephyrproject org latest reference settings index html api for runtime settings manipulation api of backend interface https docs zephyrproject org latest reference settings index html api of backend interface executing time functions https docs zephyrproject org latest reference timing functions index html api documentation virtualization inter vm shared memory https docs zephyrproject org latest reference virtualization ivshmem html api reference zephyr modules zscilib zephyr module https github com zscilib zscilib scientific computing openthread zephyr module https github com zephyrproject rtos openthread openthread micro ros zephyr module https github com micro ros micro ros zephyr module micro ros ros2 rust zephyr module https github com tylerwhall zephyr rust module for building a cargo project and linking it into a zephyr image virtualization acrn https projectacrn org qemu https www qemu org hardware abstraction supported boards https docs zephyrproject org latest boards index html releases zephyr releases https github com zephyrproject rtos zephyr releases release notes https docs zephyrproject org latest releases index html github release plan https github com zephyrproject rtos zephyr projects 9 ides js ide for zephyr os https intel github io zephyrjs ide eclipse ide https www eclipse org ide platformio ide https docs platformio org en latest integration ide pioide html platformio for clion https docs platformio org en latest integration ide pioide html platformio for clion platformio for vscode https docs platformio org en latest integration ide pioide html platformio for vscode vscode extensions trond snekvik kconfig lang https marketplace visualstudio com items itemname trond snekvik kconfig lang kconfig language support for the zephyr project in vs code trond snekvik devicetree https marketplace visualstudio com items itemname trond snekvik devicetree devicetree language support for the zephyr project in vs code platformio platformio ide https marketplace visualstudio com items itemname platformio platformio ide platformio for vscode development containers zephyr docker images https github com zephyrproject rtos docker image ci image developer image zephyr ada containers https github com zephyr ada zephyr sdk ada containers to develop ada programs based on zephyr rtos development frameworks platformio https github com platformio a professional collaborative platform for embedded development renode https github com renode renode virtual development framework for complex embedded systems blog posts zephyr website blog posts https www zephyrproject org category blog first micro ros application on zephyr rtos 2020 06 02 https www zephyrproject org first micro ros application on zephyr rtos developing zephyr rtos embedded applications on platformio and simulating on antmicro renode 2020 03 16 https www zephyrproject org developing zephyr rtos embedded applications on platformio and simulating on antmicro renode videos zephyr website videos https www zephyrproject org videos zephyr project youtube channel https www youtube com c zephyrproject videos bluetooth on zephyr overview https www youtube com watch v 1h6hb564cuu acrn hypervisor and zephyr rtos for industrial iot applications https www youtube com watch v o9ja agbp4y west overview and status https www youtube com watch v p6s0hszaua8 new shell and logger in zephyr 1 14 https www youtube com watch v jaqhhchlxxq usb support in zephyr https www youtube com watch v dj7 arpm4os zephyr power management 101 https www youtube com watch v wxomixdrlbu demand paging when software is bigger than available memory https www youtube com watch v vythqzcz5rq using opc ua with zephyr https www youtube com watch v hqdxohtafuu a deep dive into the zephyr 2 5 device model https www youtube com watch v swaxqyigeby machine learning with tensorflow lite micro on zephyr https www youtube com watch v vmdxmewu51m real time in the real world scheduler details for practical problems https www youtube com watch v 6ppjya1kj1u coredump a brief introduction and demo https www youtube com watch v gqridkxbclm logging subsystem overview https www youtube com watch v zcnzcep2dzk developing hardware for zephyr https www youtube com watch v h5aazhjgmmy using visual trace diagnostics on zephyr applications https www youtube com watch v gcunmlewggu | rtos ros2 linux | os |
Project | project information system and technologies serhii hordiievskyi https pns hneu edu ua course view php id 8314 | server |
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mbox | mbox toolchain for mobile app development version https img shields io github v release mboxplus mbox total downloads https img shields io github downloads mboxplus mbox total license https img shields io github license mboxplus mbox readme cn md english mbox is a toolchain app on macos which focuses on mobile app development it can help developers manage environments dependencies or repositories besides developers can customize their tools or workflow by developing an mbox plugin the repository this repository is the repo without any source code of mbox it is where we publish products milestones and work plans also our users search documents and submit issues here mbox uses plug in technology by adding plug ins mbox can continuously expand its capabilities there are some core plugin 1 mboxcore https github com mboxplus mbox core the mbox kernel load plugins and distribut commands 1 mboxgit https github com mboxplus mbox git provide the git support this is a kernel too the githelper and gitcmd will be usefully 1 mboxworkspace https github com mboxplus mbox workspace the workspace plugin will provide the multi repository support include feature management 1 mboxruby https github com mboxplus mbox ruby support the ruby and bundler which provide mbox bundle command 1 mboxcontainer https github com mboxplus mbox container if there are multi app in a workspace this plugin allow user select a container as the main app 1 mboxdependencymanager https github com mboxplus mbox dependency manager dependency manager plugin this is a kernel 1 mboxcocoapods https github com mboxplus mbox cocoapods extend mboxdependencymanager and mboxcontainer plugins support for the cocoapods component and container 1 mboxdev https github com mboxplus mbox dev mbox development tool the mbox develop the mbox 1 mboxdevruby https github com mboxplus mbox dev ruby develop the ruby component of mbox 1 mboxdevnative https github com mboxplus mbox dev native develop the native component of mbox include the cli 1 mboxssh https github com mboxplus mbox ssh ssh configuration support installation brew tap mboxplus homebrew tap brew install mbox you need to install homebrew https brew sh first getting started concepts and terminology e g a workspace feature container and so forth is explained here https github com mboxplus mbox wiki mbox terminology ios quick start demo https github com mboxplus mbox wiki quick start demo ios getting started for ios https github com mboxplus mbox wiki getting started ios android work in progress flutter work in progress links name description tutorial https github com mboxplus mbox wiki tutorial more advanced usage cli documentation https github com mboxplus mbox wiki cli documentation command line tools documentation contributing you have many ways to participate in this project submit bugs or feature requests https github com mboxplus mbox issues review pull requests https github com mboxplus mbox pulls refer to contributing contributing md discuss wechat 123649881 email mbox develop gmail com contact us with lark https applink feishu cn client chat chatter add by link link token fb2k24b7 a10f 40d3 85a4 cd31abc6f3e2 p align left img src doc wechat png alt wechat group width 320px p license mbox is available under gnu general public license v2 0 or later license | front_end |
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portal | notice portal has reached its end of life http flowersinthesand github io portal news 2014 10 02 portal end of life use cettia http cettia io portal the portal is a concise lightweight and feature rich javascript library for real time web application development the strong portal strong provides socket for browser based and node js based applications that need two way communication with servers but also aims to utilize a full duplex connection for modern web application development the portal greatly simplifies things essential to real time web applications like connection sharing reply heartbeat and disconnection detection the strong portal strong is designed by carefully considering known issues and best practices of real time web to provide a reliable socket based on its simple protocol website http flowersinthesand github io portal twitter http twitter com flowersits mailing list https groups google com d forum portal project test suite since this project follows test driven development tdd principles well looking at and running the test suite is a best way to understand the portal deeply every test has a title specifying a single behavior and is wrriten in qunit client js https github com flowersinthesand portal blob master test webapp unit client js tests portal and socket using dummy and mock transport server js https github com flowersinthesand portal blob master test webapp unit server js tests transports by interacting with portal server running in order to run test suite you need to have node js or write your portal server clone this repository or simply download it as a zip and extract it bash git clone https github com flowersinthesand portal git cd portal install dependencies if you are on windows you may have trouble in installing contextify see a installation guide https github com tmpvar jsdom contextify from jsdom bash npm install start server on localhost at port 8080 and 8090 both servers serve static assets but portal server is on 8080 bash node test server as browser client open http localhost 8080 http localhost 8080 for same origin or http localhost 8090 http localhost 8090 for cross origin in a browser as node js client type node test index in other console writing server a server passing the test suite is a very portal server writing portal server is not such hard one of the goals of this project from day 1 jquery stream is easy to implement in server side as simple as dealing with ajax as various transports and features are added it gets harder than dealing with ajax but still quite easy comparing to other similar projects anyway the portal server used to develop portal js is a good tutorial to write portal server and less than 2kb minified and gzipped though it doesn t matter check out server js https github com flowersinthesand portal blob master test server js | front_end |
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CHP07-Unity-step-by-step- | drajm chp07 unity step by step unity in embedded system design and robotics a step by step guide | os |
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simpleTodo | simpletodo crud application about a simple todo crud webapp and micro api service made using node js mongodb and express web framework the purpose of the project is to learn the basics of backend development by building crud apps and rest apis setup locally if you re not comfortable with command line here are tutorials using gui tools tutorials using other tools if you don t have git on your machine install it https help github com articles set up git img align right width 300 src https firstcontributions github io assets readme fork png alt fork this repository 1 star and fork this https github com nerdyvisky simpletodo git repository 2 clone your forked copy of the project git clone https github com your name simpletodo git 3 navigate to the project directory file folder cd simpletodo 4 add a reference remote to the original repository git remote add upstream https github com nerdyvisky simpletodo 5 check the remotes for this repository git remote v 6 always take a pull from the upstream repository to your master branch to keep it at par with the main project updated repository git pull upstream main 7 open index js in the root folder on line 31 replace the default string to your mongoose uri connect your mongodb uri 8 open the terminal in the root folder and run the command npm install 9 in the same terminal next run the command npm run start 9 go to http localhost 5000 in your web browser and you are ready to use the webapp api request root route http localhost 5000 api todos tech stack node js runtime express server mongodb atlas cloud database html5 sass vanilla js for client side rendering | nodejs node express expressjs mongodb mongoose mongodbatlas html-css-javascript javascript js crud-application rest-api | server |
fvim | fvim img src https github com yatli fvim raw master assets fvim png width 40 height 40 build status https dev azure com v yadli fvim apis build status yatli fvim branchname master https dev azure com v yadli fvim build latest definitionid 2 branchname master cross platform neovim front end ui built with f https fsharp org avalonia http avaloniaui net screenshot https github com yatli fvim raw master images screenshot png installation download https github com yatli fvim releases the latest release package for your system extract and run fvim for windows 7 vista 8 1 server 2008 r2 server 2012 r2 use the win7 x64 package follow these additional steps to install compatibility patches https docs microsoft com en us dotnet core install windows tabs netcore31 pivots os windows additional deps the link to the kb update is no longer functioning the issue is tracked here https github com dotnet docs issues 20459 for windows 10 use the win x64 package this version has faster startup for macos it s packaged as an app bundle unzip and drag it to your applications folder for linux debian based distributions dpkg i fvim package name deb arch linux install via aur https aur archlinux org packages fvim rpm based distributions rpm ivh fvim package name rpm fedora dnf install fvim package name rpm compile from source having dotnet sdk 6 0 x installed git clone https github com yatli fvim cd fvim dotnet publish f net6 0 c release r linux x64 self contained features theming done the neo vim way cursor color blink background image composition custom ui elements are themed with colorscheme settings and more font handling proper font rendering respects font style baseline ligatures https github com tonsky firacode etc built in support for nerd font no need to patch your fonts east asia wide glyph display with font fallback options fine grained font tweaking knobs for personal font rendering emojis gui framework hidpi support try dragging it across two screens with different dpis high performance rendering low latency 60fps on 4k display with reasonable font size gpu acceleration multi grid support try ctrl w ge to detach a window into a separate os window input method support built from scratch rich information scrollbar currently read only extend with ui server protocol https github com yatli gui widgets nvim ui widgets as neovim plugins remoting use a windows fvim frontend with a wsl neovim fvim wsl use custom neovim binary fvim nvim bin nvim appimage use the front end with a remote neovim fvim ssh user host connect to a remote neovim backend fvim connect localhost 9527 tmux like session server fvim fvr attach ssh user host as a terminal emulator fvim terminal try these bindings note fvim specific settings only work in ginit vim not init vim viml if exists g fvim loaded good old set guifont compatibility with hidpi hints if g fvim os windows g fvim render scale 1 0 set guifont iosevka slab h14 else set guifont iosevka slab h28 endif ctrl scrollwheel for zooming in out nnoremap silent c scrollwheelup set guifont cr nnoremap silent c scrollwheeldown set guifont cr nnoremap a cr fvimtogglefullscreen cr endif some fancy cursor effects viml if exists g fvim loaded fvimcursorsmoothmove v true fvimcursorsmoothblink v true endif fluent cursor https raw githubusercontent com yatli fvim master images fluent cursor gif detaching a window into an external os window with ctrl w ge ext win https raw githubusercontent com yatli fvim master images ext win gif detach as many and span them over your monitors custom popup menu entry icons see below for how to configure image https user images githubusercontent com 20684720 159672096 2630cbda 243d 46c3 b8f7 6d0a4743dffe png building from source we re now targeting net6 0 so make sure to install the latest preview sdk from the net site https dotnet microsoft com download dotnet 6 0 we re actively tracking the head of avalonia and fetch the nightly packages from myget see nuget config then simply git clone https github com yatli fvim cd fvim dotnet build c release dotnet run c release fvim specific commands the following new commands are available viml toggle between normal and fullscreen fvimtogglefullscreen cursor tweaks fvimcursorsmoothmove v true fvimcursorsmoothblink v true background composition fvimbackgroundcomposition acrylic none transparent blur or acrylic fvimbackgroundopacity 0 85 value between 0 and 1 default bg opacity fvimbackgroundaltopacity 0 85 value between 0 and 1 non default bg opacity fvimbackgroundimage c foobar png background image fvimbackgroundimagevalign center vertial position top center or bottom fvimbackgroundimagehalign center horizontal position left center or right fvimbackgroundimagestretch fill none fill uniform uniformfill fvimbackgroundimageopacity 0 85 value between 0 and 1 bg image opacity title bar tweaks fvimcustomtitlebar v true themed with colorscheme debug ui overlay fvimdrawfps v true font tweaks fvimfontantialias v true fvimfontautohint v true fvimfonthintlevel full fvimfontligature v true fvimfontlineheight 1 0 can be default 14 0 1 0 etc fvimfontsubpixel v true fvimfontnobuiltinsymbols v true disable built in nerd font symbols try to snap the fonts to the pixels reduces blur in some situations e g 100 dpi fvimfontautosnap v true font weight tuning possible valuaes are 100 900 fvimfontnormalweight 400 fvimfontboldweight 700 font debugging draw bounds around each glyph fvimfontdrawbounds v true ui options all default to v false fvimuipopupmenu v true external popup menu fvimuiwildmenu v false external wildmenu work in progress keyboard mapping options fvimkeydisableshiftspace v true disable unsupported sequence s space fvimkeyautoime v true automatic input method engagement in insert mode fvimkeyaltgr v true recognize altgr side effect is that c a key is then impossible default options workspace agnostic fvimdefaultwindowwidth 1600 default window size in a new workspace fvimdefaultwindowheight 900 detach from a remote session without killing the server if this command is executed on a standalone instance the embedded process will be terminated anyway fvimdetach breaking changes the following commands are disabled fvimuimultigrid v true per window grid system done and enabled by default fvimuitabline v false external tabline not implemented fvimuicmdline v false external cmdline not implemented fvimuimessages v false external messages not implemented fvimuitermcolors v false not implemented fvimuihlstate v false not implemented startup options usage fvim fvim args neovim args fvim args client options ssh user host start neovim remotely over ssh wsl start neovim in wsl nvim path to program use an alternative nvim program nvr target connect to a remote neovim backend the target can be an ip endpoint 127 0 0 1 9527 or a unix socket address tmp path to socket or a windows named pipe pipename setup registers fvim as a text editor and updates file association and icons requires uac elevation on windows uninstall unregisters fvim as a text editor and removes file association and icons requires uac elevation on windows fvim remoting daemon start a fvr multiplexer server can be used with nvim for alternative program pipe name override the named pipe address of the daemon when this option is not given defaults to tmp fvr main fvr id files connects to a fvr server fvr a ttach files id an integer session id to connect fvr n ew args attach attach to the first available session new create a new session with args passed to neovim can be used with ssh or wsl for connecting a remote server if neither is specified connects to the local server can be used with pipe to override the server address debug options trace to stdout trace to stdout trace to file trace to a file trace patterns filter trace output by a list of keyword strings terminal emulator terminal start as a terminal emulator terminal cmd command to run instead of the default shell the fvim arguments will be consumed and filtered before the rest are passed to neovim custom pum icons category pum text fvim nerd equivalent text t symbol https github com yatli fvim raw master assets intellisense text 16x png method symbol https github com yatli fvim raw master assets intellisense method 16x png function f symbol https github com yatli fvim raw master assets intellisense method 16x png constructor c symbol https github com yatli fvim raw master assets intellisense newclass 16x png field symbol https github com yatli fvim raw master assets intellisense field 16x png variable v symbol https github com yatli fvim raw master assets intellisense localvariable 16x png class c symbol https github com yatli fvim raw master assets intellisense class 16x png interface i symbol https github com yatli fvim raw master assets intellisense interface 16x png module m symbol https github com yatli fvim raw master assets intellisense module 16x png property p symbol https github com yatli fvim raw master assets intellisense property 16x png unit u symbol https github com yatli fvim raw master assets intellisense dimension 16x png value l symbol https github com yatli fvim raw master assets intellisense literal 16x png enum e symbol https github com yatli fvim raw master assets intellisense enumerator 16x png keyword k symbol https github com yatli fvim raw master assets intellisense intellisensekeyword 16x png snippet s symbol https github com yatli fvim raw master assets intellisense snippet 16x png color k symbol https github com yatli fvim raw master assets intellisense colorpalette 16x png file f symbol https github com yatli fvim raw master assets intellisense textfile 16x png reference r symbol https github com yatli fvim raw master assets intellisense reference 16x png folder d symbol https github com yatli fvim raw master assets intellisense folder 16x png enummember m symbol https github com yatli fvim raw master assets intellisense enumitem 16x png constant 0 symbol https github com yatli fvim raw master assets intellisense constant 16x png struct s symbol https github com yatli fvim raw master assets intellisense structure 16x png event e symbol https github com yatli fvim raw master assets intellisense event 16x png operator o symbol https github com yatli fvim raw master assets intellisense operator 16x png typeparameter t symbol https github com yatli fvim raw master assets intellisense type 16x png t so instead of populating your symbol dictionary with the nerd specific characters use textual characters fvim will pick them up and display graphical icons stored in assets intellisense instead goals keep up with the latest neovim features ergonomics improvements via gui native os integration drive the flexible and accessible ui extension method ui server protocol the idea is to establish a standard protocol for ui extensions so that the nice gui additions are not limited to one specific front end think of a front end as a ui server handling ui server protocol requests issued from front end agnostic plugins it s like language server protocol but for ui non goals electron ecosystem integration p no walled garden everything should be accessible from the neovim core which means no project explorers use a neovim plugin no custom tab lines document wells use a neovim plugin no side by side markdown viewer unless it s a neovim plugin implemented via the ui protocol extensions fellow front ends to name a few neovide https github com neovide neovide goneovim https github com akiyosi goneovim gnvim https github com vhakulinen gnvim uivonim https github com smolck uivonim firenvim https github com glacambre firenvim | neovim nvim vim editor fsharp gui ui text-editor neovim-guis dotnet avalonia xaml | front_end |
CSI-581 | csi 581 information retrieval and technology | server |
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2year | 2year study | postgresql java object-oriented-programming algorithms-and-datastructures webdevelopment | server |
the_original_problem | the original problem graphics original mit crew 01 png computer vision has a very interesting history it s roots really go all the way back to the beginning of computing and artifical intelligence in these early days it was unknown just how easy or difficult it would be to recreate the function of the human visual system a great example of this is the 1966 mit summer vision project marvin minsky and seymour papert co directors of the mit ai labratory begun the summer with some ambitious goals graphics summer project abstract 01 png minsky and papert assigned gerald sussman an mit undergraduate studunt as project lead and setup specific goals for the group around recognizing specific objects in images and seperating these objects from their backgrounds graphics summer project goals 01 png just how hard is it to acheive the goals minsky and papert laid out how has the field of computer vision advance since that summer are these tasks trivial now 50 years later do we understand how the human visual system works just how hard is computer vision and how far have we come this repository this repository is all about spending some time the with the original problem posed by minsky and papert working through this problem is a great way to begin learning computer vision graphics brick ball cylinder 2 gif the repository is broadly divided into two areas notebooks and a programming challenge the programming challenge is described in more detail below and closely follows the goals setup by minsky and papert back in 1966 the notebooks are here to give you some help along the way notebooks section notebook required reading viewing additional reading viewing code developed 1 the original problem http www welchlabs io unccv the original problem notebooks top html the summer vision project papers summer vision project pdf 2 robert s cross http www welchlabs io unccv the original problem notebooks roberts cross html only abstact and pages 25 27 machine perception of 3d solids papers roberts thesis pdf convert to grayscale roberts cross 3 image filtering http www welchlabs io unccv the original problem notebooks image filtering html how blurs filters work computerphile https youtu be c zfhwdm4ic make gaussian kernel filter 2d 4 the sobel feldman operator http www welchlabs io unccv the original problem notebooks sobel html finding the edges sobel operator computerphile https youtu be uihbwtpibxm history of sobel papers history and def of sobel operator pdf 5 the hough transform part 1 http www welchlabs io unccv the original problem notebooks hough 1 html pattern classification section 9 2 3 http a co 4o6oefr bubble chamber video https www youtube com watch v baslnz6fro8 6 the hough transform part 2 http www welchlabs io unccv the original problem notebooks hough 2 html how the hough transform was invented http www rci rutgers edu shunsun resource hough transform pdf use of the hough transformation to detect lines and curves in pictures https www cse unr edu bebis cs474 handouts houghtransformpaper pdf houghaccumulator viewing notebooks the links in the table above take you to externally hosted html exports of the notebooks this works pretty well except html won t render embedded slide shows unfortunately the best way to view the notebooks is to clone this repo and run them yourself checkout the setup instructions below https github com unccv the original problem setup animations the notebooks in this repository make frequent use of gif animations these files are pretty large so we don t store them on github and they unfortunately won t show up when viewing the notebooks via github the ideal way to view the notebooks is to clone the repo download the videos and use the recommended jupyterthemes below instructions on downloading videos are below http github com unccv the original problem downloading videos note on launching the jupyter notebooks to properly view the images and animations please launch your jupyter notebook from the root directory of this repository programming challenge instructions write a method classify py that takes in an image and returns a prediction ball brick or cylinder an example script in located in challenge sample student py your script will be automatically evaluated on a set of test images the testing images are quite similar to the training images and organized into the same difficulty categories you are allowed 10 submissions to the evaluation server which will provide immediate feedback the data easy examples graphics easy examples png grading following the progression set out the mit the summer project we ll start with easy images and move to more difficult image with more complex backgrounds as we progress for each difficulty level we will compute the average accuracy of your classifier we will then compute an average overall accuracy weighting easier examples more overall accuracy 0 5 accuracy easy 0 2 accuracy medium 1 0 2 accuracy medium 2 0 1 accuracy hard overall accuracy points 0 6 10 10 0 55 a 0 6 9 10 0 5 a 0 55 8 10 0 45 a 0 5 7 10 0 40 a 0 45 6 10 0 35 a 0 40 5 10 a 0 35 4 10 non running code 0 10 a quick note on difficulty depending on your background this challenge may feel a bit like getting thrown into the deep end if it feels a bit daunting that s ok half of the purpose of this assignement is to help you develop an appreciation for why computer vision is so hard as you may have already guessed misky sussman and papert did not reach their summer goals and i m not expecting you to either the grading table above reflects this for example if you re able to get 90 accuracy on the easy examples and simply guess randomly on the rest of the examples you ll earn 10 10 points setup the python 3 anaconda distribution https www anaconda com download is the easiest way to get going with the notebooks and code presented here optional you may want to create a virtual environment for this repository conda create n cv python 3 source activate cv you ll need to install the jupyter notebook to run the notebooks conda install jupyter you may also want to install nb conda enables some nice things like change virtual environments within the notebook conda install nb conda this repository requires the installation of a few extra packages you can install them all at once with pip install r requirements txt optional jupyterthemes https github com dunovank jupyter themes can be nice when presenting notebooks as it offers some cleaner visual themes than the stock notebook and makes it easy to adjust the default font size for code markdown etc you can install with pip pip install jupyterthemes recommend jupyter them for presenting these notebook type into terminal before launching notebook jt t grade3 cellw 90 fs 20 tfs 20 ofs 20 dfs 20 recommend jupyter them for viewing these notebook type into terminal before launching notebook jt t grade3 cellw 90 fs 14 tfs 14 ofs 14 dfs 14 downloading data for larger files such as data and videos i ve provided download scripts to download these files from welchlabs io these files can be pretty big so you may want to grab a cup of your favorite beverage to enjoy while downloading the script can be run from within the jupyter notebooks or from the terminal python util get and unpack py url http www welchlabs io unccv the original problem data data zip alternatively you can download download data manually http www welchlabs io unccv the original problem data data zip unzip and place in this directory downloading videos run the script below or call it from the notebooks python util get and unpack py url http www welchlabs io unccv the original problem videos zip alternatively you can download download videos manually http www welchlabs io unccv the original problem videos zip unzip and place in this directory | ai |
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OmniSCV | omniscv omnidirectional synthetic image generator for computer vision python implementation for a camera simulator introduction p align center img src config img fish eye png width 400 p camera models in this simulator we include two types of projection models central and no central for the central cameras we have implemented p equirectangular cylindric catadioptric cameras para catadioptric hyper catadioptric planar catadioptric fish eye cameras equiangular stereographic equi solid angle orthogonal scaramuzza kannala brandt for no central cameras we have implemented p panoramic catadioptric cameras spheric mirror conic mirror citing if you use and like our tool please cite our paper omniscv an omnidirectional synthetic image generator for computer vision https www mdpi com 684584 use instructions install requirements this code has been compiled and tested in linux using python 2 7 python 3 6 package requirements to use this image simulator first you have to have installed the following python packages the version of each package is that of development other versions might work but are not tested p unrealcv numpy version 1 16 6 math pillow version 5 1 0 stringio os scipy optimization version 1 2 1 cv2 version 4 2 0 open3d version 0 9 0 0 user guide first steps after download this repository on your own pc you have to copy the simulator folder called pack in the same directory where the unrealcv executable is located in the example we will see how this path looks like p with our pack placed in the correct directory we enter the folder and we will find several files the main script is simulator py from this script we will run the image simulator omniscv and we will be able to obtain the images from the virtual environment the other files we can find in the folder are cam loc txt in this file we will specify the locations from where we want to take the images cam rot txt in this file we will set the rotation for each location this file is prone to use for trajectories other this files will not be used by the user are for support the main program omniscv these cameras are modeled acording different mathematical models these models are explained with detail in the papers of jesus bermudez cameo http webdiis unizar es bermudez p once known the models we start to build the images of this simulator mapping our environment in a sphere arround the camera as an sphere is difficult to obtain from planar images we aproximate it with a cube map formed by 6 images in the main directions the cartesian axis x y z we build a cube map for each location in our scenario where we want to make an image to do so with our simulator we first need to set the locations where we want to take the images editing the file cam loc txt we set the different locations where we are going to get the cube maps in this file we have to write the coordinates x y z in one line and separated by white spaces for each location p align center img src config img cubemap png width 600 p defined each location in the environment from where we take the acquisition we run our main program simulator py after we run the program a menu will appear if it takes more than 5 seconds to appear we recomend to close and reopen the simulator from this menu we will be able to chose differenct functions p the first one to appear is acquisition this function makes an image acquisition from the virtual environment for the composition of central projection images p the second option is composition here we can choose which kind of image we want to compose it s divided between central and non central projection systems for the central projection systems we need to build the cube maps made with the acquisition for the non central systems since acquisition and composition are mixed you can do the composition directly without previous acquisition p next comes scenario it will give the name of the scenario to the composed images usefull for large data sets with different scenarios p and last but not least functions it s under development stil have some bugs however we can obtain ground truth information of the layout of the scene extracting the layout of the environment bash python simulator py welcome to the image simulator omniscv this simulator has been made at the university of zaragoza spain we hope you enjoy it main menu ac quisition co mposition s cenario name f unctions e xit what do you want to do downloads data set omnidirectional images from different indoor environments generated with unreal engine 4 download https unizares my sharepoint com f g personal berenguel unizar es eqru71b49gvduacvtz5u0uebvig802ntrsxzwj9ddydygw e 6mjw4p scenarios unrealcv scenarios download http docs unrealcv org en master reference model zoo html license this software is under gnu general public license version 3 gplv3 please see gnu license http www gnu org licenses gpl html for commercial purposes please contact the authors bruno berenguel baeta berenguel unizar es jes s bermudez cameo bermudez unizar es and josechu guerrero josechu guerrero unizar es note from the authors this code has not been thoroughly tested which means it may have some bugs please use with caution the authors and developers of this code want the best for the users and have gone to great lengths to make it easy to use and accessible be nice to them and enjoy their work if any problem may appear do not hesitate and we will do our best to solve it at least we will try | omnidirectional-images synthetic-images non-central-cameras central-cameras catadioptric-cameras computer-vision image-simulator fisheye-image equirectangular-panorama semantic-segmentation depth-image | ai |
large-scale-lm-tutorials | large scale language modeling tutorials with pytorch images megatron 3d png tunib pytorch transformer github https github com tunib ai large scale lm tutorials br github nbviewer https nbviewer org github tunib ai large scale lm tutorials tree main notebooks contents 1 introduction https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 01 introduction ipynb 2 motivation https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 02 motivation ipynb 3 distributed programming https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 03 distributed programming ipynb 4 overview of parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 04 overview of parallelism ipynb 5 data parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 05 data parallelism ipynb 6 pipeline parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 06 pipeline parallelism ipynb 7 tensor parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 07 tensor parallelism ipynb 8 zero redundancy optimization https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 08 zero redundancy optimization ipynb 09 multi dimensional parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 09 multi dimensional parallelism ipynb 10 additional techniques https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 10 additional techiques ipynb environments local environments linux ubuntu 18 04 lts 4 a100 gpu python 3 7 pytorch 1 9 0 cu111 docker environments docker pull pytorch pytorch 1 9 0 cuda11 1 cudnn8 devel shm size ipc host license copyright 2021 tunib inc licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license | ai |
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Shenkar-Mentoring | shenkar mentoring as part of web and cloud engineering course i have built a web application which coordinates between mentors and students br for more info about student mentor permissions click here https github com sagichubok shenkar mentoring blob master assets user 20permissions pdf br languages python javascript html css br br https shenkarmentoring pythonanywhere com mentor view img src assets mentor view gif raw true student view img src https i imgur com x3krkad gif | cloud |
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machine-learning-samples | amazon machine learning samples each subdirectory contains sample code for using amazon machine learning refer to the readme md file in each sub directory for details on using each sample targeted marketing samples these samples show how to use the amazon machine learning api for a targeted marketing application this follows the banking dataset example described in the developer guide there are three versions available targeted marketing with machine learning in java targeted marketing java targeted marketing with machine learning in python targeted marketing python targeted marketing with machine learning in scala targeted marketing scala social media and amazon mechanical turk this sample application shows how to use amazon mechanical turk to create a labeled dataset from raw tweets and then build a machine learning model using the amazon machine learning api that predicts whether or not new tweets should be acted upon by customer service the sample shows how to set up an automated filter using aws lambda that monitors tweets on an amazon kinesis stream and sends notifications whenever the ml model predicts that a new tweet is actionable notifications go to amazon sns allowing delivery to email sms text messages or other software services machine learning based social media filtering python javascript social media mobile prediction samples these samples show how to use the amazon machine learning api to make real time predictions from a mobile device there are two versions available real time machine learning predictions from ios mobile ios real time machine learning predictions from android mobile android k fold cross validation sample this sample shows how to use the amazon machine learning api to evaluate ml models using k fold cross validation k fold cross validation sample python k fold cross validation other tools a collection of simple scripts to help with common tasks machine learning tools python ml tools python support for assistance with using the amazon machine learning service or these samples please see the aws forums https forums aws amazon com forum jspa forumid 194 start 0 | ai |
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fastn | div align center contributors https img shields io github contributors fastn stack fastn color dark green issues https img shields io github issues fastn stack fastn license https img shields io github license fastn stack fastn discord https dcbadge vercel app api server enxvbmq4xt style flat https fastn com discord div div align center img src assets fastn svg width 150 alt fastn div fastn full stack web development made easy ftd is a programming language for building user interfaces and content centric websites ftd is easy to learn especially for non programmers but does not compromise on what you can build with it fastn is a web framework a content management system and an integrated development environment for ftd fastn is a webserver and compiles ftd to html css js and can be deployed on your server or on fastn cloud by fifthtry the quickest way to learn fastn is the short video course we have created expander https fastn com expander it takes you through the basics then checkout the frontend https fastn com frontend and backend https fastn com backend sections of our documentation ftd programming language for the next billion programmers ftd is designed with minimal and uniform syntax and at first glance does not even look like a programming language no quotes for string multi line strings are easy ftd amitu hello world amitu you can also write multiline messages easily no quotes and markdown is supported we have called a function named amitu with hello world as input yet it does not feel technical this is what it produces a href https fastn com ftd programming language for the next billion programmers rel nofollow img src assets img png alt img png style max width 100 width 450px a learn more about ftd programming language https fastn com ftd there are a lot of ready made ftd components available today ready made components can be imported and used ftd import fifthtry github io bling quote quote charcoal amit upadhyay label creator of ftd avatar fastn assets files images amitu jpg logo fastn assets files images logo fifthtry svg the web has lost some of the exuberance from the early 2000s and it makes me a little sad img 1 png assets img 1 png https fastn com there are a lot of ready made ftd components available today or you can create your own components creating a custom component ftd component toggle text boolean current false caption title ftd text toggle text title align self center text align center color if toggle text current d42d42 color inherited colors cta primary text background solid inherited colors cta primary base on click ftd toggle a toggle text current border radius px 5 end toggle text toggle text ftd is cool a href https fastn com or you can create your own components align center rel nofollow img src assets img 2 png alt toggle button style max width 100 width 225px a ftd s event handling capabilities can be used for form validation ajax requests etc to create fully functional frontend applications you use fastn to work with ftd we ship pre built binaries for linux mac and windows shell curl fssl https fastn com install sh bash fastn png assets fastn png https fastn com you use fastn to work with ftd integrated web development experience ftd and fastn come with package management web server opinionated design system dark mode and responsive by default if you are getting started with frontend development fastn framework takes care of a lot of things for you and all you have to focus on is your product we are working towards our own hosted web based ide version controlled code hosting and collaboration platform so you and your team gets a one stop solution for building websites fastn for static sites fastn websites can be compiled into static html js css etc and can be deployed on any static hosting providers eg github pages https fastn com github pages vercel https fastn com vercel etc ftd source code of the page you are reading ftd import fifthtry github io bling quote import fastn com ftd as ftd index my ds page overview of fastn and ftd ftd is a programming language for building user interfaces and content centric websites ftd is easy to learn especially for non programmers but does not compromise on what you can build with it ftd is a good alternative for content websites like blogs knowledge bases portfolio websites project and marketing websites etc it is cheap fast and requires little maintenance github pages png assets github pages png https fastn com fastn for static sites data driven website fetching data from api ftd import fastn processors as pr result r processor pr http url https api github com search repositories sort stars order desc q language python working with sql is breeze ftd import fastn processors as pr people processor pr package query db db sqlite select from user show person p loop people as p fastn can be used to create data driven website dashboards dynamic urls ftd fastn dynamic urls profile page url string username document profile ftd fastn can be used for creating a lot of web application backends as well upcoming wasm support we are working on wasm support so developers can extend ftd s standard libraries and offer access to more backend functionalities a href https fastn com upcoming wasm support rel nofollow img src assets wasm png alt wasm png style max width 100 width 450px a hosting dynamic sites for dynamic sites you can deploy fastn cli on the platform of your choice we ship ready made docker containers that you can add to your infrastructure fastn cloud we also offer our own hosting solution for your static and dynamic sites using fastn cloud frees you from devops needs and you get a fully integrated managed hosting solution that a non programmers can use with ease usage with nix sh nix run github fastn stack fastn in a flake nix file nix inputs flake utils url github numtide flake utils nixpkgs url github nixos nixpkgs nixpkgs unstable fastn url github fastn stack fastn outputs self flake utils nixpkgs fastn flake utils lib eachdefaultsystem system rec nix develop devshell pkgs mkshell nativebuildinputs fastn contributors all contributors list start do not remove or modify this section prettier ignore start markdownlint disable table tbody tr td align center valign top width 14 28 a href https github com arpita jaiswal img src https avatars githubusercontent com u 26044181 v 4 s 100 width 100px alt arpita jaiswal br sub b arpita jaiswal b sub a br a href https github com fastn stack fastn commits author arpita jaiswal title code a a href https github com fastn stack fastn commits author arpita jaiswal title documentation a a href example arpita jaiswal title examples a a href eventorganizing arpita jaiswal title event organizing a a href ideas arpita jaiswal title ideas planning feedback a a href maintenance arpita jaiswal title maintenance a a href mentoring arpita jaiswal title mentoring a a href https github com fastn stack fastn pulls q is 3apr reviewed by 3aarpita jaiswal title reviewed pull requests a a href tool arpita jaiswal title tools a a href https github com fastn stack fastn commits author arpita jaiswal title tests a a href tutorial arpita jaiswal title tutorials a a href video arpita jaiswal title videos a a href blog arpita jaiswal title blogposts a td td align center valign top width 14 28 a href https www fifthtry com img src https avatars githubusercontent com u 58662 v 4 s 100 width 100px alt amit upadhyay br sub b amit upadhyay b sub a br a href https github com fastn stack fastn commits author amitu title code a a href https github com fastn stack fastn commits author amitu title documentation a a href example amitu title examples a a href eventorganizing amitu title event organizing a a href ideas amitu title ideas planning feedback a a href maintenance amitu title maintenance a a href mentoring amitu title mentoring a a href https github com fastn stack fastn pulls q is 3apr reviewed by 3aamitu title reviewed pull requests a a href tool amitu title tools a a href https github com fastn stack fastn commits author amitu title tests a a href tutorial amitu title tutorials a a href video amitu title videos a a href blog amitu title blogposts a td td align center valign top width 14 28 a href https github com heulitig img src https avatars githubusercontent com u 106665190 v 4 s 100 width 100px alt rithik seth br sub b rithik seth b sub a br a href https github com fastn stack fastn commits author heulitig title code a a href https github com fastn stack fastn commits author heulitig title documentation a a href https github com fastn stack fastn commits author heulitig title tests a a href ideas heulitig title ideas planning feedback a a href https github com fastn stack fastn pulls q is 3apr reviewed by 3aheulitig title reviewed pull requests a a href maintenance heulitig title maintenance a a href blog heulitig title blogposts a td td align center valign top width 14 28 a href https github com gsalunke img 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a href https github com gargajit img src https avatars githubusercontent com u 118595104 v 4 s 100 width 100px alt ajit garg br sub b ajit garg b sub a br a href https github com fastn stack fastn commits author gargajit title code a a href https github com fastn stack fastn commits author gargajit title documentation a a href blog gargajit title blogposts a td td align center valign top width 14 28 a href https github com abrarnitk img src https avatars githubusercontent com u 17473503 v 4 s 100 width 100px alt abrar khan br sub b abrar khan b sub a br a href https github com fastn stack fastn commits author abrarnitk title code a a href https github com fastn stack fastn commits author abrarnitk title documentation a a href https github com fastn stack fastn pulls q is 3apr reviewed by 3aabrarnitk title reviewed pull requests a a href https github com fastn stack fastn commits author abrarnitk title tests a td tr tr td align center valign top width 14 28 a href https github com 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list end license this project is licensed under the terms of the bsd 3 clause license license bsd 3 clause https img shields io badge license bsd 203 clause blue svg https opensource org licenses bsd 3 clause examples the following examples are intended for testing purposes and showcase the range of capabilities of ftd language from basic to advanced use cases these examples are provided to ensure the proper functioning of ftd and to highlight its diverse features you can find the examples at the following link https fastn stack github io fastn | html-css-javascript json markdown static-site-generator rust rust-lang ft-code-repo hacktoberfest | front_end |
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