Project 1

Summary of the project:

1. Loaded and explored clinical data related to heart disease from an Excel dataset.

2. Preprocessed the data, including feature scaling and train-test splitting.

3. Applied five machine learning models (Logistic Regression, KNN, SVM, Decision Tree, Random Forest).

4. Evaluated model performance using accuracy, classification reports, and ROC-AUC scores.

5. Compared model accuracies visually, identifying Decision Tree and Random Forest as top performers.

PLease go through the attached file