Schedule
- Lectures:
- Tue & Thu 12:30pm - 1:50pm (CCIS 1-440 & Virtual)
- Tutorial (Optional):
- Thu 4:00pm - 5:00pm (CCIS 1-160 & Virtual)
- Recordings:
- Link
- Course Notes:
- Link
All course content comes from the (in progress) course notes, which were made specifically for this course. 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 will be modified throughout the term (before the content is covered).
This schedule may have small changes throughout the semester. The lectures will cover the course notes. The tutorials will go over example problems and assignment solutions. Lectures and tutorials will be recorded and posted publicly on this Youtube channel. After each lecture and tutorial a link to the lecture notes and video will be added to the lecture and tutorial table below. Most of the lectures and tutorials will be whiteboard lectures (using an iPad).
Assignments (30% total, 4.29% each)
| Assignment | Release Date | Due Date |
|---|---|---|
| Assignment 1 | Sep 13, 2024, 11:59pm MDT | Sep 20, 2024, 11:59pm MDT |
| Assignment 2 | Sep 20, 2024, 11:59pm MDT | Sep 27, 2024, 11:59pm MDT |
| Assignment 3 | Sep 27, 2024, 11:59pm MDT | Oct 04, 2024, 11:59pm MDT |
| Assignment 4 | Oct 18, 2024, 11:59pm MDT | Oct 25, 2024, 11:59pm MDT |
| Assignment 5 | Oct 25, 2024, 11:59pm MDT | Nov 01, 2024, 11:59pm MDT |
| Assignment 6 | Nov 01, 2024, 11:59pm MDT | Nov 08, 2024, 11:59pm MDT |
| Assignment 7 | Nov 22, 2024, 11:59pm MDT | Nov 29, 2024, 11:59pm MDT |
| Assignment 8 | Nov 29, 2024, 11:59pm MDT | Dec 06, 2024, 11:59pm MDT |
Lectures and Tutorials
| Week | Date | Content (Sections refer to the course notes) |
|---|---|---|
| 01 | Sep 03 | Lec 1: Chap 1 (Introducing machine learning) | Video | Intro Slides |
| 01 | Sep 05 | Lec 2: Chap 2 (Math review) | Video | Math Review Lecture Notes No Tutorial |
| 02 | Sep 10 | Lec 3: Chap 2 (Math review cont.) | Video |
| 02 | Sep 12 | Lec 4: Chap 3 (Probability) | Video | Probability Lecture Notes Tut 1: Cartesian Products | Video | Notes |
| 03 | Sep 17 | Lec 5: Chap 3 (Probability cont.) | Video |
| 03 | Sep 19 | Lec 6: Chap 3 and 4 (Probability cont. & Supervised learning) | Video Tut 2: Derivatives and probability examples | Video | Notes |
| 04 | Sep 24 | Lec 7: Chap 4 (Supervised learning) | Video | Supervised Learning Lecture Notes |
| 04 | Sep 26 | Lec 8: Chap 5 (Estimation) | Video | Estimation Lecture Notes Tut 3: Assignment 1 review | Video link on eClass in assignment 1 solutions description |
| 05 | Oct 01 | Lec 9: Chap 6 (Optimization I: Closed form solutions) | Video | Optimization I Lecture Notes |
| 05 | Oct 03 | Lec 10: Midterm exam 1 review | Video | Midterm Exam 1 Review Lecture Notes Tut 4: Assignment 2 review | Video link on eClass in assignment 2 solutions description |
| 06 | Oct 08 | Midterm exam 1 (20%): In class (12:30pm - 1:45pm in CCIS 1-440) |
| 06 | Oct 10 | Lec 11: Chap 6 (Optimization I: Closed form solutions cont.) | Video Tut 5: Assignment 3 review | Video link on eClass in assignment 3 solutions description |
| 07 | Oct 15 | Lec 12: Chap 6 (Optimization II: Gradient descent) | Video | Optimization II Lecture Notes |
| 07 | Oct 17 | Lec 13: Chap 6 (Optimization II: Gradient descent cont.) | Video Tut 6: Midterm Exam 1 review | Video link on eClass in Midterm Exam 1 solutions description |
| 08 | Oct 22 | Lec 14: Chap 7 (Evaluating models) | Video | Evaluation Lecture Notes |
| 08 | Oct 24 | Lec 15: Chap 7 (Evaluating models cont.) | Video Tut 7: Optimization Exercises | Video | Notes |
| 09 | Oct 29 | Lec 16: Chap 8 (Evaluating models cont. & MLE) | Video | MLE Lecture Notes |
| 09 | Oct 31 | Lec 17: Chap 8 (MLE cont.) | Video Tut: Cancelled |
| 10 | Nov 05 | Lec 18: Chap 8 (MAP) | Video | MAP Lecture Notes |
| 10 | Nov 07 | Lec 19: Midterm exam 2 review | Video | Midterm Exam 2 Review Lecture Notes Tut: Assignment 4 & 5 review |
| 11 | Nov 12 | READING WEEK - No Classes |
| 11 | Nov 14 | READING WEEK - No Classes |
| 12 | Nov 19 | Midterm exam 2 (20%): In class (12:30pm - 1:45pm in CCIS 1-440) |
| 12 | Nov 21 | Lec 20: Chap 9 (Binary Classification) | Video | Binary Classification Lecture Notes Tut: Cancelled |
| 13 | Nov 26 | Lec 21: Chap 9 (Multiclass Classification) | Video | Multiclass Classification Lecture Notes |
| 13 | Nov 28 | Lec 22: Chap 10 (Neural Networks) | Video | Neural Networks Lecture Notes Other resources: Playlist on NNs and backpropagation Tut: Midterm Exam 2 review | Video link on eClass in Midterm Exam 2 solutions description |
| 14 | Dec 03 | Lec 23: Chap 11 (Language Models) | Video | Language Models Lecture Notes Other resources: Video about transformers, Intro to LLMs Video |
| 14 | Dec 05 | Lec 24: Final exam review | Video | Final Exam Review Lecture Notes Tut: Assignment 7 review and exercises on neural networks | Video link on eClass in Assignment 7 description |
| Dec 18 | Final Exam (30%): 3 hours, starts at 8:30am |