Weekly plans and update for week 43

Dear all, some good news: this Wednesday we are back to in-person labs, please do use them, it is a unique opportunity in these odd times to discuss projects and many other topics related to FYS-STK, machine learning in general and more. We look forward to see you in real life. For those who cannot attend, we will run as usual our digital labs according to schedule.

Good news thus.

Else, on Thursday we will wrap up the recurrent NN discussion with examples using tensforflow and keras.

Thereafter we will look at an interesting application of deep learning and neural networks, namely solving ordinary differential equations and partial differential equations. These slides for week 43 are not yet ready, hopefully they are are ready by tomorrow (I have a bug in one of the codes, yes!).

On Friday the hope is to discuss the partial component analysis approach to reduce the dimensionality. 

Next week we move to decision trees, random forests, bagging and boosting, pretty fun methods

The slides for this week, week 43, are at https://compphysics.github.io/MachineLearning/doc/pub/week43/html/._week43-bs000.html

best wishes to you all,

the FYS-STK gang.