• Randhi Hemasree
• M.Sampath Kumar

The heart is the next major organ comparing to the brain, which has more priority in the Human body. Thus, preventing Heart diseases has become more than necessary. Good data-driven systems for predicting heart diseases can improve the entire research and prevention process, making sure that more people can live healthy lives. This is where Machine Learning comes into play. Machine Learning helps in predicting the Heart diseases, and the predictions made are quite accurate. The project involved analysis of the heart disease patient dataset with proper data processing. Then, different models were trained, and predictions are made with different algorithms KNN, Decision Tree, Random Forest, SVM, Logistic Regression etc. this is the Jupiter notebook code and I've used dataset from kaggle.com and UCI repository for various diseases-based datasets. I've used a variety of Machine Learning algorithms, implemented in Python, to predict the presence of heart disease in a patient. This is a classification problem, with input features as a variety of parameters, and the target variable as a binary variable, predicting whether heart disease is present or not.

Heart disease, Data Mining Techniques, Decision Tree, Naïve Bayesian, Support Vector Machine (SVM), K-NN classifier

"Prediction of Heart Diseases Using Machine Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.426-434, November-2020, Available :http://www.jetir.org/papers/JETIR2011193.pdf

"Prediction of Heart Diseases Using Machine Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp426-434, November-2020, Available at : http://www.jetir.org/papers/JETIR2011193.pdf