A hands-on exploration of machine learning fundamentals and applications.
- KNN - K-Nearest Neighbors for classification (diabetes dataset)
- Logistic Regression - Spam detection from email data
- Simple Linear Regression - Car price estimation and salary prediction
- Handwritten Digits - Image classification with neural networks
- Image Segmentation - Clustering-based image analysis
- Useful Code Snippets - Distance algorithms, data utilities, and helpers