Machine Learning 201

Sixteen lessons from first principles to deployment. Each lesson pairs a written reference article with a Cantonese two-host podcast, a visual guide and a short quiz. Pass the quiz to complete the lesson and unlock the Final Exam.

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All 16 lessons

01From Principles to PracticeComplete · 86%02The Math You Actually Need 03Designing Loss Functions 04Deriving the Gradients 05Optimizers In Depth 06Regularization & Generalization 07Feature Engineering & Pipelines 08Hyperparameter Tuning 09Imbalanced Data 10Feature Selection & Dimensionality Reduction 11Model Interpretability 12Time Series & Leakage 13Deep Learning in Practice 14Transfer Learning & Fine-Tuning 15Introduction to Generative Models 16ML Engineering in the LLM Era