| 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 |
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| 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
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| 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 |
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| 8 |
Fri Sep 24 |
Clustering |
Companion notebook, Clustering K-means clustering (demo) K-Means++ (demo)
IDM 8.1-8.2, ESL: 14.3 |
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| 9 |
Mon Sep 27
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More Clustering |
Companion notebook, DBSCAN (video, demo) Hierarchical Clustering Phylogenetic Trees
IDM 8.4 |
Week 3 Tutorials |
| 10 |
Wed Sep 29
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Outlier Detection |
Empirical Study
IDM 8.3, ESL 14.3.12, ML:APP 25.5 |
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| 11 |
Fri Oct 1
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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
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Assignment 2 due
a2 solutions |
| 12 |
Mon Oct 4
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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
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Gradient Descent |
Companion notebook, Gradient Descent Convex Functions |
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Fri Oct 8
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2pm class: Bonus lecture on Responsible ML by Lironne Kurzman (TA)
4pm class: Bonus lecture on Reinforcement Learning by Helen Zhang (TA) |
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Mon Oct 11 |
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THANKSGIVING - NO CLASS |
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| 14 |
Wed Oct 13
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Robust Regression |
Companion notebook, ML:APP 7.4 |
Week 5 Tutorials |
| 15 |
Fri Oct 15
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Feature Selection |
Genome-Wide Association Studies AIC, BIC
ESL 3.3 , 7.5-7 |
Assignment 3 due
a 3 solutions |
| 16 |
Mon Oct 18
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Regularization |
Companion notebook, ESL 3.4., ML:APP 7.5, AI:AMA 18.4 |
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| 17 |
Wed Oct 20
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More Regularization |
Companion notebook, RBF video RBF and Regularization video
ESL 6.7, ML:APP 13.3-4 |
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Thu Oct 21
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MIDTERM (6:00-7:30pm) |
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| 18 |
Fri Oct 22
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Linear Classifiers |
Companion notebook, Perceptron
ESL 4.5, ML:APP 8.5 |
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| 19 |
Mon Oct 25
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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
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Feature Engineering |
Gmail Priority Inbox |
Assignment 4 released |
| 21 |
Fri Oct 29
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Kernel Trick |
Companion notebook 1, Companion notebook 2, Companion notebook 3 ESL 12.3, ML:APP 14.1-4 |
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| 22 |
Mon Nov 1
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Stochastic Gradient |
Companion notebook, Stochastic Gradient
ML:APP 8.5 |
Week 7 Tutorials |
| 23 |
Wed Nov 3
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Boosting, start of MLE |
AdaBoost (video) XGBoost (video)
ML:APP 16.4 |
Max and Argmax Notes |
| 24 |
Fri Nov 5
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MLE and MAP |
Companion notebook, Maximum Likelihood Estimation
ML:APP 9.3-4 |
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Sun Nov 7
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Assignment 4 due |
| 25 |
Mon Nov 8
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Principal Component Analysis |
Companion notebook, Principal Component Analysis
ESL 14.5, IDM B.1, ML:APP 12.2 |
Assignment 5 released |
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Wed Nov 10 |
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MIDTERM BREAK - NO CLASS |
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Fri Nov 12 |
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MIDTERM BREAK - NO CLASS |
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| 26 |
Mon Nov 15
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More PCA |
Companion notebook, Making Sense of PCA SVD Eigenfaces |
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| 27 |
Wed Nov 17
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Sparse Matrix Factorization |
Companion notebook, Non-Negative Matrix Factorization (original - access from UBC)
ESL 14.6, ML: APP 13.8 |
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| 28 |
Fri Nov 19
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Recommender Systems |
Recommender Systems Netflix Prize |
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| 29 |
Mon Nov 22
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Multi-Dimensional Scaling |
Companion notebook, Nonlinear Dimensionality Reduction t-SNE demo
ESL 14.8-9, IDM B.2 |
Assignment 5 due |
| 30 |
Wed Nov 24
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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 |
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| 31 |
Fri Nov 26
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More Deep Learning |
Fortune Article Deep Learning References Alchemy
ML:APP 28.3, ESL 11.5 |
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| 32 |
Mon Nov 29
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Convolutions |
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| 33 |
Wed Dec 1
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Convolutional Neural Networks |
Companion notebook 1, Companion notebook 2, Companion notebook 3, Convolutional Neural Networks
ML:APP 28.4, ESL 11.7 |
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Fri Dec 3
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Bonus lecture |
Semi-Supervised Learning Label Propagation at Google
AlexNet |
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Mon Dec 6
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Bonus lecture |
PageRank Slides PageRank Math/Code, ESL 14.10, AI: AMA 22.3
Non-convex PL Inequality |
Assignment 6 due |