Predicting the presence of heart Disease using Machine Learning models.
Data set is availabe through Kaggle which consists of 303 rows. Reading the notebook through jupyter notebook or google collab will make it easy to understand dataset. Also, after using various machine learning model such as Linear Regression, SVM, Decision Tree etc. we have K Neighbour Classifier giving the highest probability (0.87). The dataset consists of 13 attributes and the 14th attribute being '1' and '0' which decides whether the individual shows the presence of heart disease or no respectively. Again read the notebook which has breif description of every step.