Cardiovascular disease are group of diseases which is caused due to the dysfunction of heart and blood artery and it
incorporate coronary heart disease, cerebrovascular disease, peripheral arterial disease, rheumatic heart disease, and deep vein
thrombosis and pulmonary embolism. This paper represents a model for detecting cardiovascular diseases using machine
learning algorithm. The methodology used in this research is agile methodology, in which during the stages of production
process, planning, requirements analysis, designing, coding, testing and documentation is also done in parallel. In this paper
patient dataset is used to train the model using four different machine learning algorithms (Support Vector Classifier, K-Nearest
Neighbors Classifier, Random Forest Classifier, and Decision Tree Classifier). The predictions will done through algorithm
which give the most precise result.
