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URL: http://github.com/abhishek-ch/streamlit-healthcare-ML-App

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Streamlit Healthcare Machine Learning Data App

Objective

  1. How easy is it to create a Web App using Streamlit
  2. Integrating multiple #machinelearning technologies in the same app
  3. Code reusability
  4. Streamlit functions & feature usage

of-course Dockerize!

Running the App

  1. Checkout the code
git checkout
  1. Build the docker image
docker build --tag streamlit-healthcare:1.0 .
  1. Run the docker image
docker run -it -p 8501:8501 streamlit-healthcare:1.0
  1. Browse the url

Features

  • Load Healthcare data from Kaggle https://www.kaggle.com/sulianova/cardiovascular-disease-dataset
  • Use scikit-learn ML lib to run classification.
  • Provide Tuning param options in the UI
  • Provide Switch to enable PySpark
  • Provide Pyspark MLlib options over the same data, technically one can compare the result between 2 seperate libraries
  • Plotting using Seaborn chart

Conclusion

Streamlit is essentially a very straightforward easy library to create python based Webapp. I am Convinced 👏👏👏

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Streamlit example showing Scikit Learn & Pyspark ML over Healthcare data ! Its simple !!

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docker machine-learning docker-image pyspark streamlit

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