The aim of this project is to predict heart disease using data mining techniques and machine learning algorithms.This project implements 4 classificiation models using scikit-learn: Logistic Regression, Naïve Bayes, Support Vector Classifier and Decision Tree Model to investigate their performance on heart disease datasets obtained from the UCI data repository.

All the machine learning features can be viewed here: Machine Learning features

It supports following features:

• Login/ Sign Up
• Viewing and Editing Profile
• User can enter the values of various parameters on the basis of which his risk factor will be calculated using machine learning algorithms.

1. (optional) create virtual env ex. mkvirtualenv mytest_env
2. pip install -r requirements.txt
3. python manage.py migrate
4. python manage.py runserver