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Assignments from Course Page

Date Topic Related Readings and Links Homework and Notes
Wed Sep 7
Syllabus Machine Learning Rise of the Machines Talking Machine Episode 1
Fri Sep 9
Data Exploration Gotta Catch'em all Why Not to Trust Statistics
Visualization Types Google Chart Gallery Matlab demos Other Tools
Mon Sep 12
Decision Trees A Visual Introduction to Machine Learning, Decision Trees
Entropy What make Dr. Seuss so silly?
AI:AMA 18.2-3, ESL: 9.2, ML:APP 16.2
Assignment 1 a1.zip
Notes on big-O
Getting Started with Matlab
Wed Sep 14
Learning Theory 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
Tutorial 1
Matlab Commands
Fri Sep 16
Generative Models Conditional probability (demo) Naive Bayes Probabilities and Battleship
ESL 4.3, ML: APP 2.2, 3.5, 4.1-4.2
Notes on probability
Mon Sep 19
Non-Parametric Models K-nearest neighbours Decision Theory for Darts
AI: AMA 18.8, ESL 13.3, ML:APP 1.4
Wed Sep 21
Ensemble Methods 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
Tutorial 2 t2.zip
Fri Sep 23
Clustering Clustering K-means clustering (demo) K-Means++ (demo)
IDM 8.1-8.2, ESL: 14.3
Assignment 1 due
Mon Sep 26
Density-based Clustering DBSCAN (video, demo) Norms
IDM 8.4
Assignment 2 a2.zip
Wed Sep 28
Hierarchical Clustering Hierarchical Clustering Phylogenetic Trees
IDM 8.3, ESL 14.3.12, ML:APP 25.5
Tutorial 3
Fri Sep 30
Outlier Detection Survey and Empirical Study
IDM 10.1-5
Mon Oct 3
Association Rules Association Rule Learning Apriori Amazon Product Recommendation
IDM 6.1-6.3, ESL 14.2
Wed Oct 5
Linear Regression Linear Regression (demo, 2D data, 2D video) Least Squares
Partial Derivatives Gradient
ESL 3.1-2, ML:APP 7.1-3, AI:AMA 18.6
Tutorial 4
Notes on Linear Algebra
Fri Oct 7
Non-Linear Regression Fluid Simulation
ESL 5.1, 6.3, and 6.7
Assignment 2 due
Linear/Quadratic Gradients
Wed Oct 12
Regularization RBF video RBF and Regularization video
ESL 3.4, ML:APP 7.5, AI:AMA 18.4
Assignment 3 a3.zip
Tutorial 5
Fri Oct 14
Gradient Descent Gradient Descent
ML:APP 7.4
Mon Oct 17
Logistic Regression Gmail Priority Inbox
ESL 4.4, ML:APP 8.1-3, AI:AMA 18.9
Wed Oct 19
Support Vector Machines Support Vector Machines
ESL 4.5 and 12.1-2, ML:APP 14.5
Assignment 3 due
Tutorial 6
Fri Oct 21
Kernel Methods ESL 12.3, ML:APP 14.1-4
Mon Oct 24
Stochastic Gradient Stochastic Gradient
ML:APP 8.5
Wed Oct 26
Feature Selection ESL 3.3
Fri Oct 28
Midterm
Mon Oct 31
L1-Regularization Maximum Likelihood Estimation
ESL 3.4, ML:APP 13.3-4
Assignment 4 a4.zip
Wed Nov 2
Multi-Class Regression ML:APP 8.3.7 and 9.3-5, ESL 4.4 Tutorial 8
Fri Nov 4
Principal Component Analysis Principal Component Analysis
ESL 14.5, IDM B.1, ML:APP 12.2
Mon Nov 7
More PCA SVD Eigenfaces
Wed Nov 9
Sparse Matrix Factorization Non-Negative Matrix Factorization
ESL 14.6, ML: APP 13.8
Tutorial 9
Mon Nov 14
Recommender Systems Recommender Systems Netflix Prize Assignment 5 a5.zip
Assignment 4 due
Wed Nov 16
Multi-Dimensional Scaling Nonlinear Dimensionality Reduction
ESL 14.8-9, IDM B.2
Tutorial 10
Fri Nov 18
Neural Networks Google Video Fortune Article
ML:APP 16.5, ESL 11.1-4, AI: AMA 18.7
Assignment 6 a6.zip
Mon Nov 21
Deep Learning Web book
ML:APP 28.3, ESL 11.5
Wed Nov 23
Convolutional Neural Networks Convolutional Neural Networks AlexNet
ML:APP 28.4, ESL 11.7
Tutorial 11
Fri Nov 25
More CNNs Assignment 5 due
Mon Nov 28
Ranking PageRank Slides, PageRank math/code
ESL 14.10, ML:APP 9.7, AI: AMA 22.3
Wed Nov 30
Semi-Supervised Learning Semi-Supervised Learning Label Propagation at Google Tutorial 12
Fri Dec 2
Course Review/Preview Assignment 6 due