Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression

 

 

 

Plans for week 35

The main topics are:

  1. Brief repetition from last week
  2. Discussions of the equations for ordinary least squares
  3. Discussion on how to prepare data and examples of applications of linear regression
  4. Material for the lecture on Monday: Mathematical interpretations of linear regression
  5. Monday: Ridge and Lasso regression and Singular Value Decomposition

Reading recommendations:

  1. These lecture notes
  2. Video of lecture
  3. Video for exercises week 35
  4. Goodfellow, Bengio and Courville, Deep Learning, chapter 2 on linear algebra and sections 3.1-3.10 on elements of statistics (background)
  5. Raschka et al on preprocessing of data, relevant for exercise 3 this week, see chapter 4.
  6. For exercise 1 of week 35, the book by A. Aldo Faisal, Cheng Soon Ong, and Marc Peter Deisenroth on the Mathematics of Machine Learning, may be very relevant. In particular chapter 5 at URL"https://mml-book.github.io/" (section 5.5 on derivatives) is very useful for exercise 1 this coming week.