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DDA3020

DDA3020: Machine Learning Notes

CUHK-Shenzhen · Spring 2026

CUHK-Shenzhen DDA3020 Machine Learning notes, Spring 2026: regression, SVMs, neural networks, clustering, and EM. Free PDF and LaTeX source.

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Topics covered

  • Foundations: Probability, information theory, linear algebra, and optimization.
  • Supervised learning: Linear and logistic regression, support vector machines, tree-based methods, and neural networks including CNNs and RNNs.
  • Model evaluation: Overfitting, underfitting, the bias–variance tradeoff, and performance evaluation.
  • Unsupervised learning: K-means, Gaussian mixture models, and expectation-maximization.