Plans for week 35, August 25-29
Dear all, welcome back to FYS-STK3155/4155. We hope you've had a great weekend. This week we plan to continue our discussion of linear regression, with an emphasis on its derivation and links to mathematical interpretations. We plan also to start our discussion of Ridge and Lasso regression. The plans are
Brief repetition from last week
o Discussions of the equations for ordinary least squares (OLS)
o Discussion on how to prepare data and examples of applications of linear regression
o Mathematical interpretations of OLS
o Introduction of Ridge and Lasso regression
Reading recommendations:
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The weekly lecture notes
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Goodfellow, Bengio and Courville, Deep Learning, chapter 2 on linear algebra
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Raschka et al on preprocessing of data, relevant for exercise 3 this week, see chapter 4.
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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.
Note that the lecture notes contain also material about the singular value decomposition (SVD) algorithm. We may not be able to cover the SVD analysis during this week. It will then be postponed to next week, with an analysis of gradient methods as well.
The lecture notes this week, and the exercises as well are at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/intro.html, just scroll down on the content part (left side).
Best wishes to you all,
Morten et al