In-depth analysis( bivariate and multivariate) and visualisation of the Heart Disease UCI dataset, which contains 303 samples of patients involving heart diseases. > Performed extensive data analysis by using popular python libraries such as Pandas, Seaborn , Sci-kit Learn and Matplotlib. > Analysed the datasets and the multiple relations of different features and plotted distribution plots, histograms and heatmaps > Chose an appropriate Logistic Regression model for the classification problem using SK Learn library. > Performed cross-validation on the dataset to get an average accuracy score of 83%