Weekly update for week 43

Dear all,
here comes the weekly update for FYS-STK3155/4155.

Lab this week: We continue with project 2.  We would also like to remind you that we have (for those of you who cannot physically) digital labs at 815-10 and 1415-16. Feel free to use this also if you are attending the in-person labs. Today for example, for the lab from 815-10 in F?397 (which is a self-study lab), this can serve as an alternative. 

Last week we discussed convolutional neural networks. This week we will summarize our discussions of CNNs and discuss so-called Recurrent Neural Networks (of great interest for studies of tie series, and language sequences of variable length). As reading background , we recommend Goodfellow et al in their chapter 10. We also recommend Geron's chapter 14 and the lecture notes (some parts will be wrapped up later today).
We recommend also taking a look at Goodfellow et al and their chapters 11 and 12. These chapters contain many practical hints and advices on deep learning methods.

After recurrent neural networks, we will discuss (Friday) principal components analysis and clustering as methods to reduce the dimensionality of the problems. This material is covered by the lecture notes, see 
https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/chapter8.html and https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/Clustering.html.

For the rest of the semester, our focus will be on decision trees, random forests, bagging, boosting and finally support vector machines. 

In the meantime, best wishes to you all,
Morten et al