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UBC CPSC 330: Applied Machine Learning (2024W1)
Things you should know
Syllabus
CPSC 330 Documents
Course Learning Objectives
Lectures
Lecture 1: Course Introduction
Lecture 2: Terminology, Baselines, Decision Trees
Lecture 3: Machine Learning Fundamentals
Lecture 4:
\(k\)
-Nearest Neighbours and SVM RBFs
Lecture 5: Preprocessing and
sklearn
pipelines
Lecture 6:
sklearn
ColumnTransformer
and Text Features
Lecture 7: Linear Models
Lecture 8: Hyperparameter Optimization and Optimization Bias
Lecture 9: Classification metrics
Lecture 10: Regression metrics
Lecture 12: Ensembles
Lecture 13: Feature importances and model transparency
Lecture 14: Feature engineering and feature selection
Lecture 15: K-Means Clustering
Lecture 16: More Clustering
Lecture 17: Recommender Systems
Lecture 18: Introduction to natural language processing
Lecture 19: Multi-class classification and introduction to computer vision
Lecture 20: Time series
Lecture 21: Survival analysis
Lecture 22: Communication
Lecture 24: Deployment and conclusion
Final exam preparation: guiding questions
Appendix A: Demo of feature engineering for text data
Appendix B: Multi-class, meta-strategies
Section slides
Section 101
Lecture 1: Course Introduction
Lecture 2: Terminology, Baselines, Decision Trees
Lecture 3: Machine Learning Fundamentals
Lecture 4:
\(k\)
-Nearest Neighbours and SVM RBFs
Lecture 5: Preprocessing and
sklearn
pipelines
Lecture 6:
sklearn
ColumnTransformer
and Text Features
Lecture 7: Linear Models
Lecture 8: Hyperparameter Optimization and Optimization Bias
Lecture 9: Classification metrics
Lecture 10: Regression metrics
Lecture 12: Ensembles
Lecture 13: Feature importances and model transparency
Lecture 14: Feature engineering and feature selection
Lecture 15: K-Means Clustering
Lecture 16: More Clustering
Lecture 17
Lecture 18
Lecture 19: Multi-class classification and introduction to computer vision
Lecture 20: Time series
Lecture 21: Survival analysis
Lecture 22: Communication
Lecture 23
Section 102
Lecture 1
Lecture 2
Lecture 3
Lecture 4
Lecture 5
Lecture 6
Lecture 7
Lecture 8
Lecture 9
Lecture 10
Lecture 11
Lecture 12
Lecture 13
Lecture 14
Lecture 15
Lecture 16
Lecture 17
Lecture 18
Lecture 19
Lecture 20
Lecture 21
Lecture 22
Lecture 23
Lecture 24
Section 103
Lecture 1
Lecture 2
Lecture 3
Lecture 4
Lecture 5
Lecture 6
Lecture 7
Lecture 8
Lecture 9
Lecture 11
Lecture 12
Lecture 13
Lecture 14
Lecture 15
Lecture 16
Lecture 17
Lecture 18
Lecture 19
Lecture 20
Lecture 21
Lecture 22
Lecture 23
Lecture 24
Attribution
LICENSE
Index
