The project implements 3 linear models and one deep learning model: Naïve Bayes, Support Vector Machine, and K-Nearest Neighbors network to investigate their performance on diabetes, heart, and Parkinson’s disease datasets obtained from the UCI data repository.
Prediction of multiple diseases- diabetes, heart, Parkinson’s, liver, breast cancer, malaria, pneumonia, and liver diseases under one – machine learning-based web app.
High accuracy, as a result of various different models, and rigorous training.
Peek into Working :->
