Diabetes Predictor Web App

How the project works

• Using the dataset we do EDA and find a suitable model
• The model turn out to be random forest
• aplying train test spilt on the dataset
• Model is fit on training data following eda for observation
• Then model is fit on out of sample data or testing data
• In the backend we make a form that accepts parameters from users
• These parameters are passed in an array
• The model is pickled and passed to the backend.
• the pkl model is fit on the array and prediction is rendered to html file.
• here we put a condition case that if predition is this then render this result.
• The HTML and CSS files are binded in the backend itself

Dependencies

• ML model ===>>> Scikit Learn
• Backend ===>>> Flask(Python)
• Frontend ===>>> HTML & CSS

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Contributors please read contribution guide before submitting a PR

Shoutout and credits to Anuj Vyas who also deployed this project on heroku, do check out his profile