Readings
Students are expected to read the corresponding sections about a class’s topic from notes before class as each class will discuss each topic in more detail and address questions about the material.
All readings are from the (in progress) machine learning notes. These are designed to be short, so that you can read every chapter. I recommend avoiding printing these notes, since later parts of the notes are likely to be modified (even if only a little bit).
Schedule
This schedule is tentative, and is likely to change throughout the semester. Most of the lectures will be whiteboard lectures.
| Week | Date | Topic | Readings |
|---|---|---|---|
| 1 | September 2, 2021 | Introduction to the Course | Assignment #1 released with associated code and instructions Thought questions #1: - read Chapters 1, 2 and 3 from the notes.pdf |
| 2 | September 7, 2021 | Probability | |
| 2 | September 9, 2021 | Multivariate Probability | |
| 3 | September 14, 2021 | (Move to Whiteboard, Lecture Notes uploaded after class.) A First Step in Estimation: Sample Averages, Concentration Inequalities, Confidence and Sample Complexity | |
| 3 | September 16, 2021 | Bias and Variance, start Formalizing Parameter Estimation | Thought questions #1 due on Thursday, Sept. 16 Thought questions #2: - read Chapters 4, 5 and 6 from the notes.pdf |
| 4 | September 21, 2021 | Intro to Optimization | |
| 4 | September 23, 2021 | MAP and MLE, and Bayesian estimation | Assignment #1 due on Friday, Sept 24 Assignment #2 released with associated code |
| 5 | September 28, 2021 | Bayesian estimation (cont.) and conjugate priors | |
| 5 | September 30, 2021 | Class Cancelled for National Day for Truth and Reconciliation | Thought questions #2 due Sept. 30 Thought questions #3: - read Chapters 7, 8 and 9 from the notes.pdf |
| 6 | October 5, 2021 | More example of posteriors, and MLE for univariate regression | |
| 6 | October 7, 2021 | Stochastic Gradient Descent and more on stepsize selection | Stepsize script used in class script_stepsizes.py |
| 7 | October 12, 2021 | Quiz Review Slides | |
| 7 | October 14, 2021 | In-class Quiz | |
| 8 | October 19, 2021 | Introduction to Prediction and Optimal Predictors | Assignment #2 due on Monday, Oct. 18 Assignment #3 released with associated code. |
| 8 | October 21, 2021 | Finish Optimal Predictors start Linear Regression and Optimization | Thought questions #3 due on Oct 21 Thought questions #4: - read Chapters 10, 11 and 12 from the notes.pdf |
| 9 | October 26, 2021 | Finish Linear Regression and Optimization | |
| 9 | October 28, 2021 | Polynomial Regression, and Generalization Error and Overfitting | |
| 10 | November 2, 2021 | Evaluation of Learned Models and Hypothesis Testing, start Regularization | |
| 10 | November 4, 2021 | Bias, variance and generalization error | Thought questions #4 due |
| 11 | November 9, 2021 | No classes, Reading Week | Assignment #3 due on Monday, Nov. 9 Assignment #4 released with associated code. |
| 11 | November 11, 2021 | No classes, Reading Week | |
| 12 | November 16, 2021 | Midterm Review | |
| 12 | November 18, 2021 | Midterm | |
| 13 | November 23, 2021 | Logistic regression and classification | Demo comparing Linear Regression and Logistic Regression |
| 13 | November 25, 2021 | Finish Logistic regression, then do Bayesian linear regression | |
| 14 | November 30, 2021 | Finish contrasting prediction intervals and confidence intervals, then Review class on whiteboard. | |
| 14 | December 2, 2021 | Final Review slides highlighting which topics are tested, with Q&A session. | |
| 15 | December 7, 2021 | Cancelled, Practice Final session scheduled for December 14 | Assignment #4 due on Friday, December 8. |
| Final | Tuesday, December 21, 2021, 9:00 a.m. | Final Exam | 2 hours. |