Plans for the week of September 16-20

Dear all, welcome back to a new exciting week with machine learning! Our plans this week are as follows, with lecture notes at for example https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week38/ipynb/week38.ipynb:

Material for the lecture on Monday September 16.

• Logistic regression as our first encounter of classification methods. From binary cases to several categories.

• Start gradient and optimization methods

Suggested reading and videos

• Readings and Videos:

  • Hastie et al 4.1, 4.2 and 4.3 on logistic regression

  • Raschka et al, pages 53-76 on Logistic regression and pages 37-52 on gradient optimization

  • For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.

  • Video on Logistic regression

  • Yet another video on logistic regression

  • Video on gradient descent

Plans for the lab session and material for the active learning sessions on Tuesday and Wednesday.

• Repetition from last week on the bias-variance tradeoff

• Resampling techniques, cross-validation examples included here, see also the lectures from last week on the bootstrap method

• Exercise for week 38 on the bias-variance tradeoff, see also the video from the lab session from week 37 at https://youtu.be/omLmp_kkie0

• Work on project 1, in particular resampling methods like cross-validation and bootstrap.

Best wishes to you all,

Fahimeh, Ida, Karl Henrik, Mia,, Morten, Odin, and Sigurd