Schedule
- Lectures:
- Tue & Thu 2:00pm - 3:20pm (ETLC E1-001 & Virtual)
- Recordings:
- Will be posted in eClass. Also check out last term's recordings
- Course Notes:
- Link (from previous term by Vlad Tkachuk and likely to be adapted)
All course content comes from the (in progress) course notes, which were made specifically for this course last term and are likely to be adapted for this term. 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 might 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 assignment solutions. Lectures and tutorials will be recorded and posted on eClass. Also check out the recordings from previous term. After each lecture a link to the lecture notes will be added here (videos to eClass). Most of the lectures and tutorials will be whiteboard lectures (using an iPad).
Assignments (25% total, 3.57% each)
| Assignment | Release Date | Due Date |
|---|---|---|
| Assignment 1 | Jan 17, 2025, 11:59pm MDT | Jan 24, 2025, 11:59pm MDT |
| Assignment 2 | Jan 24, 2025, 11:59pm MDT | Jan 31, 2025, 11:59pm MDT |
| Assignment 3 | Jan 31, 2025, 11:59pm MDT | Feb 07, 2025, 11:59pm MDT |
| Assignment 4 | Feb 28, 2025, 11:59pm MDT | Mar 07, 2025, 11:59pm MDT |
| Assignment 5 | Mar 07, 2025, 11:59pm MDT | Mar 14, 2025, 11:59pm MDT |
| Assignment 6 | Mar 14, 2025, 11:59pm MDT | Mar 21, 2025, 11:59pm MDT |
| Assignment 7 | Mar 28, 2025, 11:59pm MDT | Apr 04, 2025, 11:59pm MDT |
| Assignment 8 | Apr 04, 2025, 11:59pm MDT | Apr 11, 2025, 11:59pm MDT |
Lectures
| Week | Date | Content (Sections refer to the course notes) |
|---|---|---|
| 01 | Jan 07 | Lec 1: Chap 1 (Introducing machine learning) | intro slides |
| 01 | Jan 09 | Lec 2: Chap 2 (Math review) | math review |
| 02 | Jan 14 | Lec 3: Chap 2 (Math review cont.) | math review cont. |
| 02 | Jan 16 | Lec 4: Chap 3 (Probability) | probability |
| 03 | Jan 21 | Lec 5: Chap 3 (Probability cont.) | probability cont. before class | probability cont. after class |
| 03 | Jan 23 | Lec 6: Chap 3 (Probability cont.) | probability cont. before class | probability cont. after class |
| 04 | Jan 28 | Lec 7: Chap 4 (Supervised learning) | supervised learning before class | supervised learning after class |
| 04 | Jan 30 | Lec 8: Chap 5 (Estimation) | estimation before class | estimation after class |
| 05 | Feb 04 | Lec 9: Chap 6 (Optimization I: Closed form solutions) | optimization 1 before class | optimization 1 after class |
| 05 | Feb 06 | Lec 10: Midterm exam 1 review | midterm 1 review |
| 06 | Feb 11 | Midterm exam 1 (22.5%): In class (2:00pm - 3:15pm in ETLC E1-001) | midterm 1 formula sheet | practice midterm 1 |
| 06 | Feb 13 | Lec 11: Chap 6 (Optimization I: Closed form solutions cont.) | optimization 1 cont. before class | optimization 1 cont. after class |
| 07 | Feb 18 | READING WEEK - No Classes |
| 07 | Feb 20 | READING WEEK - No Classes |
| 08 | Feb 25 | Lec 12: Chap 6 (Optimization II: Gradient descent) | optimization 2 before class | optimization 2 after class |
| 08 | Feb 27 | Lec 13: Chap 6 (Optimization II: Gradient descent cont.) | optimization 2 cont. after class |
| 09 | Mar 04 | Lec 14: Chap 7 (Evaluating models) | optimization 2 cont. after class | evaluation |
| 09 | Mar 06 | Lec 15: Chap 7 (Evaluating models cont.) |
| 10 | Mar 11 | Lec 16: Chap 8 (Evaluating models cont. & MLE) | evaluation cont. before class | MLE after class |
| 10 | Mar 13 | Lec 17: Chap 8 (MLE cont.) | MLE cont. before class | MAP before class |
| 11 | Mar 18 | Lec 18: Chap 8 (MLE cont. & MAP) |
| 11 | Mar 20 | Lec 19: Midterm exam 2 review |
| 12 | Mar 25 | Midterm exam 2 (22.5%): In class (2:00pm - 3:15pm in ETLC E1-00) |
| 12 | Mar 27 | Lec 20: Chap 9 (Binary Classification) |
| 13 | Apr 01 | Lec 21: Chap 9 (Multiclass Classification) |
| 13 | Apr 03 | Lec 22: Chap 10 (Neural Networks) |
| 14 | Apr 08 | Lec 23: Chap 11 (Language Models) |
| 14 | Apr 10 | Lec 24: Final exam review |
| Apr 23 | Final Exam (30%): 3 hours, starts at 1:00pm (tentative) |