Time and Location:
Monday, Wednesday 9:30am10:50am, NVIDIA Auditorium
Class Videos:
Current quarter's class videos are available here for SCPD students and here for nonSCPD students.
Event  Date  Description  Materials and Assignments  

Lecture 1  9/23  Introduction and Basic Concepts  
Lecture 2  9/25  Supervised Learning Setup. Linear Regression. 
Class Notes


Assignment  9/26  Problem Set 0 [link]. Due Wednesday, Oct 2 at 11:59pm  
Section 1  9/28  Friday Lecture: Linear Algebra.  Notes  
Lecture 3  9/30 
Weighted Least Squares. Logistic Regression. Netwon's Method Perceptron. Exponential Family. Generalized Linear Models. 
Class Notes


Lecture 4  10/2  
Assignment  10/2  Problem Set 1 [link]. Due Wednesday, Oct 16 at 11:59pm  
Section 2  10/4  Friday Lecture: Probability  Notes  
Lecture 5  10/7  Gaussian Discriminant Analysis. Naive Bayes.  
Lecture 6  10/9 
Laplace Smoothing. Support Vector Machines. 
Class Notes


Section 3  10/11  Friday Lecture: Python and Numpy  Notes  
Lecture 7  10/14  Support Vector Machines. Kernels.  
Lecture 8  10/16  Neural Networks  1  Class Notes  
Assignment  10/16 
Problem Set 2 [link]. Due Wednesday, Oct 30 at 11:59pm


Section 4  10/18  Friday Lecture: Evaluation Metrics 
Notes


Project  10/18  Project proposal due 10/18 at 11:59pm.  
Lecture 9  10/21  Neural Networks  2  
Lecture 10  10/23  Bias  Variance. Regularization. Feature / Model selection. 
Class Notes


Section 5  10/25  Friday Lecture: Deep Learning 
Notes


Lecture 11  10/28  Practical Advice for ML projects. 
Class Notes


Assignment  10/30 
Problem Set 3 [link]. Due Wednesday, Nov 13 at 11:59pm 

Lecture 12  10/30  KMeans. GMM (non EM). Expectation Maximization.  Class Notes  
Section 6  11/1  Friday Lecture: Midterm Review 
Class Notes


Lecture 13  11/4  Expectation Maximization. Factor Analysis. 
Class Notes


Midterm  11/5  The midterm details are posted on Piazza.  
Lecture 14  11/6  Principal and Independent Component Analysis.  Class Notes  
Section 7  11/8  Friday Lecture: Decision Trees. Boosting. Bagging.  Class Notes  
Lecture 15  11/11  Weak Supervision 
Class Notes


Lecture 16  11/13  
Assignment  11/13 
Problem Set 4
[link]
. Due Wednesday, Dec 4 at 11:59pm 

Section 8  11/15  Friday Lecture: On critiques of Machine Learning 
Class Notes


Project  11/15  Project milestones due 11/15 at 11:59pm.  
Lecture 17  11/18  Value Iteration and Policy Iteration 
Class Notes


Lecture 18  11/20  Bias and Variance 
Class Notes


Lecture 19  12/2  Learning Theory 
Class Notes


Lecture 20  12/4  Course wrapup. Beyond CS229 Guest Lectures! Details [link]  
Project  12/11  Poster submission deadline, due 12/11 at 11:59pm (no late days).  
Project  12/12  Poster presentations from 8:3011:30am. Venue and details to be announced.  
Project  12/13  Project final report due 12/13 at 11:59pm (no late days).  
Supplementary Notes  
Other Resources
