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A web app for beginners in Machine Learning and Data Science to fiddle with different parameters of various ML algorithms on the Framingham Heart Disease dataset.

Home Page: https://manual-parameter-tuner.streamlit.app/

License: MIT License

Python 97.26% Shell 1.00% CSS 1.57% Procfile 0.17%
heart-disease-dataset framingham tuner streamlit-webapp data-science machine-learning hyperparameter-tuning parameters ml-algorithms python3

manual-parameter-tuner's Introduction

Manual Parameter Tuner

A web app for beginners in Machine Learning and Data Science to fiddle with different parameters of various ML algorithms on the Framingham Heart Disease dataset.

UI Streamlit App

Functionalities

Manually tune parameters of different ML algorithms to get the best result on the Framingham Heart Disease dataset.

Detailed description of the Dataset and the functionalities are present in the Website itself.

Check out the published Website here:

https://manual-parameter-tuner.streamlit.app/


Instructions to run the web app locally

  • Pre-requisites:

    • Python 3.6 or 3.7 or 3.8
    • Dependencies from requirements.txt
  • Directions to Install

    • First clone this repository onto your system.
    • Then, create a Virtual Environment and install the packages from requirements.txt:
    • Navigate to this repository, create a Virtual Environment and activate it:
    cd path/to/cloned/repo
    python3 -m venv env
    source env/bin/activate

    Install the python dependencies from requirements.txt:

    pip install -r requirements.txt
  • Directions to Execute

    From the same project directory, run the following command in the terminal -

    streamlit run app.py

    This will prompt a localhost and you can view and make changes to the source file locally.

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