Heart-disease

In this project, we were given the patient data and the evaluation was to predict whether the patient has heart disease or not. It was a bi-classification problem with 2 classes, true or false. We used the Random Forest Classifier machine learning model to train our data while setting the best parameters to achieve the highest level of accuracy and avoid over- and underfitting. We even assessed our model through different sklearn metrics.