This repository holds the code, data, and documentation for my capstone project, completed during the IBM Skillsuild Edunet Foundation Internship. The project focuses on predicting the presence of heart disease using machine learning techniques
Highlights:
- Developed a Machine Learning Model: Leverages Logistic Regression, SVC, KNeighbors Classifier, Non-Linear ML Algorithms, Decision Tree Classifier, Random Forest Classifier, Gradient Boosting Classifier to predict the likelihood of heart disease based on patient data.
- Utilized heart disease dataset (https://www.kaggle.com/datasets/johnsmith88/heart-disease-dataset): Trained the model on a well-established dataset containing relevant patient characteristics.
- Evaluated Model Performance: Employed metrics to assess the model's effectiveness in predicting heart disease.
- Clear and Documented Code: The codebase adheres to best practices for readability and maintainability.