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predico's Introduction

Predico: The smart health predictor

Overview

To create a smart disease prediction system made using traditional machine learning algorithms and to create an user interface using streamlit.

Technical aspect

  1. Created and evaluated a model using descision tree, random forrest and gradient boost.
  2. Building and hosting a streamlit based web app on heroku (coming soon)

Directory tree

โ”œโ”€โ”€ dataset
โ”‚   โ”œโ”€โ”€ test_data.csv
โ”‚   โ””โ”€โ”€ training_data.csv
โ”œโ”€โ”€ saved_models
โ”‚   โ””โ”€โ”€ random_f.joblib
โ”œโ”€โ”€ app.py
โ”œโ”€โ”€ main.py
โ”œโ”€โ”€ config.yaml
โ”œโ”€โ”€ LICENSE
โ””โ”€โ”€ README.md

To do

  1. Create the heroku hosting files
  2. Add dark mode to streamlit UI using overflow
  3. Creating UI to read into given diagnosis

Technologies used

Read a brief report of the following project here

Contributions are welcome please consider making a pull request!

predico's People

Contributors

madhav-somanath avatar

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