Weekly plans and update for week 38

Hi all, this is the weekly fys-stk3155/4155 digest. Last week we started discussing gradient methods, a central element of all ML methods. We started at the end of Friday's lecture to discuss logistic regression as well. The main focus this week is indeed on logistic regression, theory and examples as well as a continued discussion on gradient methods. project 2 deals with a classification problem and we will develop code for both logistic regression as well as for neural networks. We begin with neural networks next week. 

This Thursday 

we continue our discussion on Logistic regression as well as a further discussion of gradient methods, see the slides at 

https://compphysics.github.io/MachineLearning/doc/pub/LogReg/html/._LogReg-bs000.html for logistic regression and https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/._Splines-bs000.html for gradient methods.  The material on logistic regression is covered by Hastie et al, see chapter 4.4 in particular.

Best wishes to everybody,

Hanna, Lucas, Morten and Stian