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Video of the lectures is available via the echo360 portal of the course. A link is provided on Canvas and Piazza.
Topics | Reading | Assignments | |
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Week 1: August 23,25 | |||
Tuesday | Course introduction ( slides). | Sections 1.1 and 1.2 in the textbook | |
Thursday | Course introduction (continued). | Sections 1.1 and 1.2 in the textbook | Assignment 1 is available. |
Week 2: August 30, Sept 1 | |||
Tuesday | Linear models ( slides). Short intro to LaTex and python [ notes ]. | Chapter 1, and Section 3.1 in the textbook | |
Thursday | Linear models and the perceptron algorithm (cont). | Chapter 1, and Section 3.1 in the textbook | Assignment 2 is available. |
Week 3: September 6,8 | |||
Tuesday | code for the perceptron. Linear regression ( slides). | Chapter 3.2 | |
Thursday | Logistic regression ( slides). | Chapter 3.3 | |
Week 4: September 13,15 | |||
Tuesday | Overfitting ( slides) | Chapters 2.3,4.1 | |
Thursday | Regularization and model selection ( slides) | Chapter 4 | |
Week 5: September 22,24 | |||
Tuesday | Model selection and cross validation (continued) | Chapter 4 | Assignment 3 is available. |
Thursday | Support vector machines ( slides) | Chapter e-8 |
…
Week 15: December 6,8 | |||
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Tuesday | Course summary | ||
Thursday | Poster session |