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This is a demo project to show how to make predictions using Machine Learning RandomForestClassifier model and its deployment using Flask API.

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Machine Learning Demo Deployment

This is a demo project to show how to make predictions using Machine Learning RandomForestClassifier model and its deployment using Flask API.

Table of Contents:

Project has two major parts:

  • exploration: This contains jupyter notebook with Heart Disease Data Analysis.
    • data: Csv-file with Heart Disease data
    • model: Python script with RandomForestClassifier Model and pickled model as a file using pickle.
  • webapp: Flask Application with template to make predictions using simple and friendly user interface.
    • tests: This contains some test for webapp.

Installation:

To run this project it is recommended to setup a conda (or virtual) environment by using requirements.txt file.

conda create --name <env> --file <requirements.txt> 
conda activate <your path> 

Run webapp:

export FLASK_APP=webApp/heart_disease_webapp
flask run

execute tests:

pytest -v tests/tests.py

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This is a demo project to show how to make predictions using Machine Learning RandomForestClassifier model and its deployment using Flask API.

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