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README.md

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----
-title: Resume Parser POC
-emoji: 🐨
-colorFrom: gray
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
-license: openrail
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Resume-Parser-END-TO-END-V2-
+Upgraded the UI
+
+**APP LINK**: https://resume-parser-ver2.herokuapp.com/
+
+# Resume-Parser-END-TO-END
+
+**Tools Used**:- Custom Named Entity Recognition (NER), Spacy, NLP.
+
+**Data Source**:LinkedIn Resume Summaries
+
+**Extracting Information**: Experience, Skills, In-progress(Education. Certification, Awards, Organization, Person)
+
+**ML Deploy**: Streamlit and Deployed on Heroku

app.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[2]:
+
+
+
+import numpy as np
+import joblib
+
+
+
+import streamlit as st
+import pandas as pd
+import numpy as np
+import altair as alt
+import pydeck as pdk
+
+# SETTING PAGE CONFIG TO WIDE MODE
+st.set_page_config(layout="wide")
+
+
+st.title('Resume Parser')
+
+
+'##### Instructions:- Select text from LinkedIn Summary Section Only '
+
+txt = st.text_input('Resume summary to Analyze', '''
+Been a CS Graduate, I am a Data Science enthusiast 
+with a good understanding of Machine Learning algorithms 
+Techniques such as Regression, Classification, and Clustering, along with 
+Computer Vision and NLP. Self Thaught Python Programmer. 
+Has a good understanding of SQL and also has good Data Visualisation skills, 
+and has worked with tools like Tableau and Python libraries such as Numpy and Pandas,
+Scikit learn, Matplotlib and Seaborn. 
+I'm highly passionate about Data Science and intending to pursue a career in Big data/Data Scientist. 
+github link - https://github.com/pramod1998-hash
+     ''')
+
+model = joblib.load(open('modelf.pkl', 'rb'))
+
+
+
+st.write('**Summary Submitted**:\n', txt)
+
+int_features = [txt]
+#st.write(int_features)
+docs=list(model.pipe(int_features))
+lst=[]        
+for doc in docs:        
+    for entity in doc.ents:
+        #st.write((entity.text,entity.label_))
+        lst.append((entity.text,entity.label_))
+
+output = lst
+
+df = pd.DataFrame(
+    lst)
+
+st.write("### OUTPUT:-")
+st.dataframe(df)
+
+st.write("*Note: So far our AI has been train to extract only skill and experience. This AI can be trained further for extraction required information* ")
+#st.write(output)
+
+
+
+
+

modelf.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:30c43b26972b2cb9ebab2a104d6fa6c462bb313e76c56ff8c83fa865e8f73e85
+size 15487513

requirements.txt

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+streamlit==1.5.0
+spacy==3.0
+openpyxl
+pandas
+numpy>=1.9.2
+scipy>=0.15.1
+scikit-learn>=0.18
+matplotlib>=1.4.3
+joblib==0.16.0