• Mar. 28. Slides for today's lectures (on CNN) and code for the lab sessions are available here.

• Mar. 26. Lecture notes on Convolutional Neural Networks have been uploaded. Please read it before the lectures.

• Mar. 26. Slides for today's lectures (on Neural Networks) and code for the lab session are available here.

• Mar. 21. Lecture notes on neural networks and backpropagation have been uploaded. Please read these materials before the lectures.

• Mar. 19. This Thursday morning (the lecture times on March 21), we will discuss in detail the results of A1 (linear regression). We will focus on explaining the common misunderstandings/mistakes observed when marking A1, followed by the correct answers and how they are obtained.

• Mar. 19. Slides and code for today's lab session are available here.

• Mar. 14. Slides for today's lectures on decision trees and random forest have been uploaded.

• Mar. 12. Lecture notes on decision trees and random forest and performance metrics are available. You're highly encouraged to read them before the lectures.

• Mar. 7. Slides for this morning's lectures (on SVM) and code/slides for this afternoon's lab session (on SVM) are available here. The second assignment (A2) has also started.

• Mar. 5. Lecture notes on support vector machine are available. You're highly encouraged to read them before the lectures.

• Feb. 29. Slides for lectures Bayesian classification and logistic regression have been uploaded.

• Feb. 27. Lecture notes on Bayesian classification and logistic regression are available. You're highly encouraged to read these materials before the lectures.

• Feb. 22. Slides for lectures clustering and neareast neighbor classification have been uploaded.

• Feb. 16. Lecture notes on clustering and nearest neighbor classification are available. You're highly encouraged to read these materials before the lectures.

• Feb. 15. The first assignment (i.e., A1: linear regression) is available on BrightSpace under 'Assignments'. Note: you must join a group to access the assignment.

• Feb. 15. Slides and letcutre notes for today's lectures on 'introduction to machine learning' and 'linear regression and gradient descent' have been uploaded, which can be found here.

• Jan. 10. The first lecture/meeting will be on the 15th of Feb. 2024. Check out the course calendar.

• Jan. 9. The course website is online.

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