ML201 · 4 credits

Machine Learning

Supervised and unsupervised learning, model evaluation, regularisation and an introduction to neural networks.

Lecturer: Minh Tran

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Chapter 1: Supervised Learning
- What Is Machine Learning?Course overview, the main kinds of learning problems and the standard training workflow.
- Linear RegressionModel, loss function, the normal equation and gradient descent — the foundation for every model that follows.
Chapter 2: Classification
- Logistic RegressionFrom linear scores to probabilities with the sigmoid function and the cross-entropy loss.