Abstract: Machine Learning has recently played an important part in the healthcare business, and among all of the major diseases, sentiment ailment is one of the furthermost crucial and vital diseases to forecast. The quantity of instances is rapidly increasing every day. Because it has been initiate that four individuals amongst the ages of 30 and 50 have a stroke every minute, we are spread over appliance scholarship procedures to alleviate this problem.

The heart disease dataset was utilised by Kaggle for this project. This research examines and displays employing a variety of machine-learning categorization techniques, such as naive Bay Probabilistic Forest, and SVM, in identifying cardiovascular conditions, and others. Later on, the Stacking Ensemble Learning Technique is utilised to progress the routine of our classification models.

Cardiology, Data Analysis, Data Mining, Diseases, Pattern Classification, Support Vector Machine, Heart Disease Prediction, Artifical Nueral Network (ANN).

| DOI: 10.17148/IARJSET.2023.107105