Sadiksmart0 commited on
Commit
f8e1476
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1 Parent(s): 5f4fd95

Update app.py

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Files changed (1) hide show
  1. app.py +10 -13
app.py CHANGED
@@ -118,7 +118,7 @@ with st.expander("PROJECT 1: Analysis of Ligue 1 From 2010-2021"):
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  st.markdown("""
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  - Analyzed 12 season for Ligue 1
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  - Used plotly express and dash for visualization.
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- - Pandas to load and analyes
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  - Streamlit for the web app.
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  """)
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  st.markdown("[Project CODE](https://github.com/sadiksmart0/DataVisualizationProject)")
@@ -131,10 +131,9 @@ with st.expander("PROJECT 1: Analysis of Google play Apps"):
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  st.subheader('Analysis of Google play Apps')
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  st.write("This project intends to ...")
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  st.markdown("""
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- - Collaborated and developed a state-of-the-art deep learning model using BERT and gensims Doc2Vec for recognizing song emotion and give recommendations based on that given lyrics, song title and artist name.
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- - Deployed the model on Heroku and serve the it using FastApi.
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- - Develop and deployed the app on streamlit.
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- - Presented the work as part of our masters thesis.
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  """)
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  # # st.image("https://static.streamlit.io/examples/dice.jpg")
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  st.markdown("[Project CODE](https://github.com/sadiksmart0/Android-App-Market/blob/main/Android%20App%20Market.ipynb)")
@@ -144,10 +143,9 @@ with st.expander("PROJECT 1: Analysis of Netflix movies"):
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  st.subheader('Analysis of Netflix movies')
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  st.write("This project intends to ...")
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  st.markdown("""
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- - Collaborated and developed a state-of-the-art deep learning model using BERT and gensims Doc2Vec for recognizing song emotion and give recommendations based on that given lyrics, song title and artist name.
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- - Deployed the model on Heroku and serve the it using FastApi.
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- - Develop and deployed the app on streamlit.
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- - Presented the work as part of our masters thesis.
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  """)
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  # # st.image("https://static.streamlit.io/examples/dice.jpg")
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  st.markdown("[Project CODE](https://github.com/sadiksmart0/Netflix-Movies/blob/main/Netflix-Movies.ipynb)")
@@ -157,10 +155,9 @@ with st.expander("PROJECT 1: Analysis of Nobel Prize Winners"):
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  st.subheader('Analysis of Nobel Prize Winners')
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  st.write("This project intends to ...")
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  st.markdown("""
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- - Collaborated and developed a state-of-the-art deep learning model using BERT and gensims Doc2Vec for recognizing song emotion and give recommendations based on that given lyrics, song title and artist name.
161
- - Deployed the model on Heroku and serve the it using FastApi.
162
- - Develop and deployed the app on streamlit.
163
- - Presented the work as part of our masters thesis.
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  """)
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  # # st.image("https://static.streamlit.io/examples/dice.jpg")
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  st.markdown("[Project CODE](https://github.com/sadiksmart0/Nobel-Prize/blob/main/Nobel_Prize.ipynb)")
 
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  st.markdown("""
119
  - Analyzed 12 season for Ligue 1
120
  - Used plotly express and dash for visualization.
121
+ - Pandas to load and run analysis.
122
  - Streamlit for the web app.
123
  """)
124
  st.markdown("[Project CODE](https://github.com/sadiksmart0/DataVisualizationProject)")
 
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  st.subheader('Analysis of Google play Apps')
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  st.write("This project intends to ...")
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  st.markdown("""
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+ - Analyzed google play apps.
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+ - Utilized matplotlib for visualization.
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+ - Utilized jupyter notebook for the analysis.
 
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  """)
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  # # st.image("https://static.streamlit.io/examples/dice.jpg")
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  st.markdown("[Project CODE](https://github.com/sadiksmart0/Android-App-Market/blob/main/Android%20App%20Market.ipynb)")
 
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  st.subheader('Analysis of Netflix movies')
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  st.write("This project intends to ...")
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  st.markdown("""
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+ - Analyzed Netflix movies dataset.
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+ - Utilized matplotlib for visualization.
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+ - Utilized jupyter notebook for the analysis.
 
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  """)
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  # # st.image("https://static.streamlit.io/examples/dice.jpg")
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  st.markdown("[Project CODE](https://github.com/sadiksmart0/Netflix-Movies/blob/main/Netflix-Movies.ipynb)")
 
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  st.subheader('Analysis of Nobel Prize Winners')
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  st.write("This project intends to ...")
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  st.markdown("""
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+ - Analyzed Nobel prize winners from the dataset.
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+ - Utilized matplotlib for visualization.
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+ - Utilized jupyter notebook for the analysis.
 
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  """)
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  # # st.image("https://static.streamlit.io/examples/dice.jpg")
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  st.markdown("[Project CODE](https://github.com/sadiksmart0/Nobel-Prize/blob/main/Nobel_Prize.ipynb)")