End to end Heart-Disease-Classification

Web app for predicting heart disease using machine learning

Data :

I got the data from UCI Machine Learning Repositry : https://archive.ics.uci.edu/ml/datasets/heart+disease.

EDA :

I made some eda and data visualizations to understand my data more and check for any outliers.

Modeling :

After getting my data ready I chose KNN, Random forest classifier and logestic regression and tested each one of them, numbers showed that logestic regression is the best of them then I proceeded with hyperparameter tuning to increase model performance and reached to 86% accuracy

Deployment :

I used flask for creating my app and deployed it using herouko (https://heartdiseasepredictorx.herokuapp.com/)