CPSC 340: Machine Learning and Data Mining (2021W2)

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

Course documents

• syllabus
• homework submission instructions
• textbooks and online resources
• CPSC 340 vs. CPSC 330 vs. CPSC 440

Schedule

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

#	Date	Slides	Instructor	Related Readings and Links	Homework and Notes
1	Mon Jan 10	Motivation and Syllabus	Both	What is Machine Learning? Machine Learning Rise of the Machines Talking Machine Episode 1	a1 posted
2	Wed Jan 12	Exploratory Data Analysis	Jeff	Companion notebook, Gotta Catch'em all Why Not to Trust Statistics Visualization Types Google Chart Gallery Other Tools
3	Fri Jan 14	Decision Trees	Jeff	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	Mon Jan 17	Fundamentals of Learning	Jeff	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	Wed Jan 19	Probabilistic Classifiers	Mi Jung	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	Fri Jan 21	Non-Parametric Models	Mi Jung	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	Mon Jan 24	Ensemble Methods	Jeff	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	Wed Jan 26	Clustering	Jeff	Companion notebook, Clustering K-means clustering (demo) K-Means++ (demo) IDM 8.1-8.2, ESL: 14.3
9	Fri Jan 28	More Clustering	Jeff	Companion notebook, DBSCAN (video, demo) Hierarchical Clustering Phylogenetic Trees IDM 8.4 Week 3 Tutorials
10	Mon Jan 31	Outlier Detection	Jeff	Empirical Study IDM 8.3, ESL 14.3.12, ML:APP 25.5
11	Wed Feb 2	Least Squares	Mi Jung	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	Fri Feb 4	Nonlinear Regression	Jeff	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	Mon Feb 7	Gradient Descent	Jeff	Companion notebook, Gradient Descent Convex Functions
	Wed Feb 9	Guest Lecture:
14	Fri Feb 11	Robust Regression	Mi Jung	Companion notebook, ML:APP 7.4	Week 5 Tutorials
15	Mon Feb 14	Feature Selection	Mi Jung	Genome-Wide Association Studies AIC, BIC ESL 3.3 , 7.5-7	Assignment 3 due a 3 solutions
16	Wed Feb 16	Regularization	Mi Jung	Companion notebook, ESL 3.4., ML:APP 7.5, AI:AMA 18.4
17	Fri Feb 18	More Regularization	Mi Jung	Companion notebook, RBF video RBF and Regularization video ESL 6.7, ML:APP 13.3-4
	Feb 21 -- 25		MIDTERM BREAK
18	Mon Feb 28	Linear Classifiers	Mi Jung	Companion notebook, Perceptron ESL 4.5, ML:APP 8.5
19	Wed Mar 2	More Linear Classifiers	Mi Jung	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	Fri Mar 4	Feature Engineering	Jeff	Gmail Priority Inbox	Assignment 4 released
21	Mon Mar 7	Kernel Trick	Mi Jung	Companion notebook 1, Companion notebook 2, Companion notebook 3 ESL 12.3, ML:APP 14.1-4
22	Wed Mar 9	Stochastic Gradient	Jeff	Companion notebook, Stochastic Gradient ML:APP 8.5	Week 7 Tutorials
23	Fri Mar 11	Boosting, start of MLE	Mi Jung	AdaBoost (video) XGBoost (video) ML:APP 16.4	Max and Argmax Notes
24	Mon Mar 14	MLE and MAP	Mi Jung	Companion notebook, Maximum Likelihood Estimation ML:APP 9.3-4
25	Wed Mar 16	Principal Component Analysis	Mi Jung	Companion notebook, Principal Component Analysis ESL 14.5, IDM B.1, ML:APP 12.2	Assignment 5 released
26	Fri Mar 18	More PCA	Mi Jung	Companion notebook, Making Sense of PCA SVD Eigenfaces	Week 8 Tutorials
27	Mon Mar 21	Sparse Matrix Factorization	Mi Jung	Companion notebook, Non-Negative Matrix Factorization (original - access from UBC) ESL 14.6, ML: APP 13.8
28	Wed Mar 23	Recommender Systems	Mi Jung	Recommender Systems, Netflix Prize, Nonlinear Dimensionality Reduction, t-SNE demo, ESL 14.8-9, IDM B.2
29	Fri Mar 25	Deep Learning	Jeff	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	Mon Mar 28	More Deep Learning	Jeff	Fortune Article Deep Learning References, Alchemy ML:APP 28.3, ESL 11.5
31	Wed Mar 30	Convolutions	Jeff	Companion notebook
32	Fri Apr 1	Convolutional Neural Networks	Jeff	Companion notebook, Convolutional Neural Networks ML:APP 28.4, ESL 11.7	Week 10 Tutorials
33	Mon Apr 4	More CNNs	Jeff
	Wed Apr 6	Guest Lecture
34	Fri Apr 8	Conclusion	both		Assignment 6 due, No tutorials this week.