1. Clone the repository

2. Create a virtual environment using python (v3.9.2) and activate it

3. Install the dependencies using pip

   pip install -r requirements.txt

4. Run Flask app

   flask run

5. It will run on localhost IP on port 5000.

UCI Pima Indians dataset

• Flask framework
• Jupyter Notebook
• Pickle
• HTML5, CSS3

1. Home Page

2. Prediction

1. Data visualization
2. Preprocessing
3. Performing Hyperparameter tuning
4. Using multiple algorithms to select the best one

We selected the random forest model which gave us an accuracy of 83.12%. The jupyter notebook is shared in the repository itself.

Vedant Puranik
Sahil Naphade