CPSC 340: Machine Learning and Data Mining (2021W1)

This is the public-facing portion of the course website; also see the Canvas course for links to the course Piazza site, lecture recordings, and submitting assignments.

Course documents

Schedule

Note: In the timetable below, the textbook codes (such as "AI:AMA") are defined here.

#	Date	Slides	Related Readings and Links	Homework and Notes
1	Wed Sep 8	Motivation and Syllabus	What is Machine Learning? Machine Learning Rise of the Machines Talking Machine Episode 1	a1 posted
2	Fri Sep 10	Exploratory Data Analysis	Companion notebook, Gotta Catch'em all Why Not to Trust Statistics Visualization Types Google Chart Gallery Other Tools
3	Mon Sep 13	Decision Trees	A Visual Introduction to Machine Learning, Decision Trees Entropy AI:AMA 18.2-3, ESL: 9.2, ML:APP 16.2	Big-O Notes, Week 1 Tutorials
4	Wed Sep 15	Fundamentals of Learning	Companion notebook, 7 Steps of Machine Learning IID Cross-validation Bias-variance No Free Lunch AI: AMA 18.4-5, ESL 7.1-7.4, 7.10, ML:APP 1.4, 6.5	Course Notation Guide
5	Fri Sep 17	Probabilistic Classifiers	Conditional probability (demo) Naive Bayes Probabilities and Battleship ESL 4.3, ML: APP 2.2, 3.5, 4.1-4.2	Assignment 1 due a1 solutions Probability Notes Probability Slides
6	Mon Sep 20	Non-Parametric Models	Companion notebook, K-nearest neighbours Decision Theory for Darts Norms AI: AMA 18.8, ESL 13.3, ML:APP 1.4	Assignment 2 posted Week 2 Tutorials
7	Wed Sep 22	Ensemble Methods	Companion notebook, Ensemble Methods Random Forests Empirical Study Kinect AI: AMA 18.10, ESL: 7.11, 8.2, 15, 16.3, ML: APP 6.2.1, 16.2.5, 16.6
8	Fri Sep 24	Clustering	Companion notebook, Clustering K-means clustering (demo) K-Means++ (demo) IDM 8.1-8.2, ESL: 14.3
9	Mon Sep 27	More Clustering	Companion notebook, DBSCAN (video, demo) Hierarchical Clustering Phylogenetic Trees IDM 8.4	Week 3 Tutorials
10	Wed Sep 29	Outlier Detection	Empirical Study IDM 8.3, ESL 14.3.12, ML:APP 25.5
11	Fri Oct 1	Least Squares	Companion notebook, Linear Regression (demo, 2D data, 2D video) Least Squares Essence of Calculus Partial Derivative Gradient ESL 3.1-2, ML:APP 7.1-3, AI:AMA 18.6	Assignment 2 due a2 solutions
12	Mon Oct 4	Nonlinear Regression	Why should one learn machine learning from scratch? Essence of Linear Algebra Matrix Differentiation Fluid Simulation (video) ESL 5.1, 6.3	Linear Algebra Notes Linear/Quadratic Gradients, Week 4 Tutorials
13	Wed Oct 6	Gradient Descent	Companion notebook, Gradient Descent Convex Functions
	Fri Oct 8	2pm class: Bonus lecture on Responsible ML by Lironne Kurzman (TA) 4pm class: Bonus lecture on Reinforcement Learning by Helen Zhang (TA)
	Mon Oct 11		THANKSGIVING - NO CLASS
14	Wed Oct 13	Robust Regression	Companion notebook, ML:APP 7.4	Week 5 Tutorials
15	Fri Oct 15	Feature Selection	Genome-Wide Association Studies AIC, BIC ESL 3.3 , 7.5-7	Assignment 3 due a 3 solutions
16	Mon Oct 18	Regularization	Companion notebook, ESL 3.4., ML:APP 7.5, AI:AMA 18.4
17	Wed Oct 20	More Regularization	Companion notebook, RBF video RBF and Regularization video ESL 6.7, ML:APP 13.3-4
	Thu Oct 21		MIDTERM (6:00-7:30pm)
18	Fri Oct 22	Linear Classifiers	Companion notebook, Perceptron ESL 4.5, ML:APP 8.5
19	Mon Oct 25	More Linear Classifiers	Companion notebook, Support Vector Machines ESL 4.4, 12.1-2, ML:APP 8.1-3, 9.5 14.5, AI:AMA 18.9	Week 6 Tutorials
20	Wed Oct 27	Feature Engineering	Gmail Priority Inbox	Assignment 4 released
21	Fri Oct 29	Kernel Trick	Companion notebook 1, Companion notebook 2, Companion notebook 3 ESL 12.3, ML:APP 14.1-4
22	Mon Nov 1	Stochastic Gradient	Companion notebook, Stochastic Gradient ML:APP 8.5	Week 7 Tutorials
23	Wed Nov 3	Boosting, start of MLE	AdaBoost (video) XGBoost (video) ML:APP 16.4	Max and Argmax Notes
24	Fri Nov 5	MLE and MAP	Companion notebook, Maximum Likelihood Estimation ML:APP 9.3-4
	Sun Nov 7			Assignment 4 due
25	Mon Nov 8	Principal Component Analysis	Companion notebook, Principal Component Analysis ESL 14.5, IDM B.1, ML:APP 12.2	Assignment 5 released
	Wed Nov 10		MIDTERM BREAK - NO CLASS
	Fri Nov 12		MIDTERM BREAK - NO CLASS
26	Mon Nov 15	More PCA	Companion notebook, Making Sense of PCA SVD Eigenfaces	Week 8 Tutorials
27	Wed Nov 17	Sparse Matrix Factorization	Companion notebook, Non-Negative Matrix Factorization (original - access from UBC) ESL 14.6, ML: APP 13.8
28	Fri Nov 19	Recommender Systems	Recommender Systems, Netflix Prize, Nonlinear Dimensionality Reduction, t-SNE demo, ESL 14.8-9, IDM B.2
29	Mon Nov 22	Deep Learning	Companion notebook, Google Video What is a Neural Network? Interactive Guide ML:APP 16.5, ESL 11.1-4, AI: AMA 18.7	Assignment 5 due, Week 9 Tutorials
30	Wed Nov 24	More Deep Learning	Fortune Article Deep Learning References, Alchemy ML:APP 28.3, ESL 11.5
31	Fri Nov 26	Convolutions	Companion notebook
32	Mon Nov 29	Convolutional Neural Networks	Companion notebook, Convolutional Neural Networks ML:APP 28.4, ESL 11.7	Week 10 Tutorials
33	Wed Dec 1	More CNNs
	Fri Dec 3	2pm class: Bonus lecture on CNN details 4pm class: Bonus lecture on generative adversarial nets (GANs) and distances between distributions
34	Mon Dec 6	Conclusion		Assignment 6 due, No tutorials this week.

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CPSC 340: Machine Learning and Data Mining (2021W1)

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