This is an old revision of the document!
March 20: A4grader.tar linked to on the A4 web page has been updated. It longer checks for QDArelated functions.
March 18: There will be no lecture class on Wednesday, March 22nd. Chuck's office hours on March 22nd are cancelled.
Lecture videos are available at this CS480 video recordings site.
Week  Topic  Material  Reading  Assignments 

Week 1: Jan 17  Jan 20  Overview. Intro to machine learning. Python.  01 Course Overview, 02 Matrices and Plotting,  The Great A.I. Awakening, by Gideon LewisKrause, NYT, Dec 14, 2016. Section 1 of Scipy Lecture Notes  
Week 2: Jan 23  Jan 27  Probability distributions and regression.  03 Linear Regression, 04 Gaussian Distributions 
Week  Topic  Material  Reading  Assignments 

Week 3: Jan 30  Feb 3  Probabilistic Linear Regression. Ridge regression. Data partitioning. Online, incremental regression.  05 Fitting Gaussians, 06 Probabilistic Linear Regression, 07 Linear Ridge Regression and Data Partitioning, 08 SamplebySample Linear Regression  A1 Linear Regression due Monday, January 30th at 10:00 PM.  
Week 4: Feb 6  Feb 10  Regression with fixed nonlinearities. Nonlinear regression with neural networks. Feb 10: Guest Speaker Mike Morain, Machine Learning at Amazon, UK.  09 Linear Regression with Fixed Nonlinear Features, 10 Nonlinear Regression with Neural Networks  
Week 5: Feb 13  Feb 17  Neural Networks  10 Nonlinear Regression with Neural Networks, 11 More Nonlinear Regression with Neural Networks  A2 Ridge Regression with KFold CrossValidation due Monday, February 13th at 10:00 PM. Here are examples of good A2 reports. 

Week 6: Feb 20  Feb 24  Neural Networks. Autoencoders. Guest lectures by our GTA, Jake Lee.  12 Autoencoder Neural Networks  
Week 7: Feb 27  Mar 3  Recurrent Neural Networks. Conditional probabilities and Bayes Rule  13 Recurrent Neural Networks 14 Introduction to Classification  A3 Neural Network Regression due Wednesday, March 1st at 10:00 PM. Here are examples of good A3 reports. 
Week  Topic  Material  Reading  Assignments 

Week 8: Mar 6  Mar 10  Classification. LDA and QDA. Linear and Nonlinear Logistic Regression.  15 Classification with Linear Logistic Regression 16 Classification with Nonlinear Logistic Regression Using Neural Networks  
Week 9: Mar 20, Mar 24 No class March 22nd.  Classification. Analysis of Trained Networks. Bottleneck Networks. HandDrawn Digit Classification.  17 Analysis of Neural Network Classifiers and Bottleneck Networks 18 Digits  
Week 10: Mar 27  Mar 31  Convolutional Neural Networks. Reinforcement Learning.  19 Convolutional Neural Networks 20 Introduction to Reinforcement Learning  Reinforcement Learning: An Introduction, by Richard Sutton and Andrew Barto. 2nd edition draft. Online and free. 
Week  Topic  Material  Reading  Assignments 

Week 11: Apr 3  Apr 7  Reinforcement Learning. Twoplayer games.  21 Reinforcement Learning for Two Player Games  Reinforcement Learning: An Introduction, by Richard Sutton and Andrew Barto. 2nd edition draft. Online and free.  A4 Classification with LDA and Logistic Regression due Wednesday, April 5th at 10:00 PM. Here are examples of good A4 reports. Project Proposal due Friday, April 7th at 10:00 PM. 
Week 12: Apr 10  Apr 14  Neural networks as Q functions.  22 Reinforcement Learning with Neural Network as Q Function Faster RL by Pretraining  The Dark Secret at the Heart of AI The Tiny Changes That Can Cause AI to Fail  
Week 13: Apr 17  Apr 21  Unsupervised Learning. Dimensionality reduction.  23 Linear Dimensionality Reduction 24 Nonlinear Dimensionality Reduction with Digits Example 25 KMeans Clustering 26 Hierarchical Clustering  
Week 14: Apr 24  Apr 28  A5 Control a Marble with Reinforcement Learning due Monday, April 24th at 10:00 PM. 
Week  Topic  Material  Reading  Assignments 

Week 15: May 1  May 5  
Finals Week: May 8  May 11  Final project due Tuesday, May 9, 10:00 PM. Details on report requirements will be posted here soon. 