Plans for week 38
Dear all, we hope you are all doing well and had a great weekend.
This week we start with a discussion of logistic regression and our first encounter with classification problems. This serves also as a motivation for introducing gradient methods since we no longer end up with nice analytical expressions for the optimal parameters beta.
The plans for this week are
Material for the active learning sessions on Tuesday and Wednesday.
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Lecture from last week on the bias-variance tradeoff
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Resampling techniques, cross-validation examples included here, see also the lectures from last week on the bootstrap method
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Exercise for week 38, see also the whiteboard notes from week 37 at https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep14.pdfLinks to an external site.
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Work on project 1, in particular resampling methods like cross-validation and bootstrap.
Material for the lecture on Thursday September 21.
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Logistic regression as our first encounter of classification methods. From binary cases to several categories.
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Start gradient and optimization methods
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Readings and Videos:
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Hastie et al 4.1, 4.2 and 4.3 on logistic regression
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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.
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See also the whiteboard notes from week 37 at https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep14.pdfLinks to an external site. for a discussion and derivation of the bias-variance tradeoff.
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Yet another video on logistic regressionLinks to an external site.
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For the lab sessions we recommend revisiting the material from last week on resampling methods, as these form the last part to be included in the project. The exercises this week can again be included in the project. The exercises next week focus on writing the report and deal simply with you writing an abstract, an introduction and adding references. Hopefully that will get you all started with writing the report.
Best wishes to you all,
Adam, Daniel,, Fahimeh, Ida, Karl Henrik, Mia and Morten