This notebook implements some foundation machine learning and data science concepts by exploring the problem of heart disease classification.
The goal of this is to mimic what a data scientist or machine learning engineer would produce as proof of concept.
Classification involes deciding whether a sample is part of one class or another (single-class classification). If there are multiple class options, it's referred to as multi-class classification.
- Exploratory Data Analysis
- Model Training
- Model Evaluation
- Model Comparison
- Model fine-tuning
- Feature Importance
- Cross-Validation
- Evaluating and Reporting Results