Machine Learning from Scratch

Master the full ML pipeline, from linear algebra, calculus, and probability fundamentals to implementing regression, classification, clustering, and neural networks from scratch in NumPy, then scaling to scikit-learn, PyTorch, and real-world datasets with proper train/val/test splits, cross-validation, and model evaluation metrics.