Student Resources
PDF lecture notes and materials for all modules
Part A
Foundations of Statistical Learning
Module 01
What is Statistical Machine Learning?
▶ Open module
Module 02
Model Accuracy: Training vs Test Error
▶ Open module
Module 03
Bias-Variance Tradeoff in Depth
▶ Open module
Part B
Linear Models (Brief Review)
Module 04
Simple Linear Regression
▶ Open module
Module 05
Multiple Linear Regression
▶ Open module
Module 06
Model Assessment: R², F-test, CIs
▶ Open module
Module 07
Logistic Regression
▶ Open module
Part C
Classification Methods
Module 08
Linear Discriminant Analysis (LDA)
▶ Open module
Module 09
QDA and Naive Bayes
▶ Open module
Module 10
K-Nearest Neighbours
▶ Open module
Part D
Performance Measures
Module 11
Regression Metrics: MSE, RMSE, MAE, R²
▶ Open module
Module 12
Classification Metrics: Confusion Matrix, Precision, Recall, F1
▶ Open module
Module 13
ROC Curve, AUC, and Model Calibration
▶ Open module
Module 14
Cross-Validation
▶ Open module
Part E
Resampling and Model Selection
Module 15
The Bootstrap
▶ Open module
Module 16
Subset Selection: Best, Forward, Backward
▶ Open module
Module 17
Ridge Regression and Lasso
▶ Open module
Part F
Tree-Based Methods
Module 18
Introduction to Decision Trees: CART
▶ Open module
Module 19
Classification Trees and Pruning
▶ Open module
Module 20
Ensemble Methods: A Brief Overview
▶ Open module
Part G
Dimensionality Reduction
Module 21
Principal Component Analysis (PCA)
▶ Open module
Module 22
PCR and Partial Least Squares
▶ Open module
Part H
Unsupervised Learning
Module 23
K-Means Clustering
▶ Open module
Module 24
Hierarchical Clustering
▶ Open module
Part I
Search Algorithms
Module 25
Search Algorithms I: Problem Formulation, BFS and DFS
▶ Open module
Module 26
Search Algorithms II: Informed Search, Best-First and A*
▶ Open module
Part J
Big Data
Module 27
Big Data and Hadoop
▶ Open module
Part K
Neural Networks and Practice
Module 28
Neural Networks and Deep Learning
▶ Open module
Module 29
Applied Case Study: A Complete Machine Learning Pipeline
▶ Open module