Plans for week 45, November 3-7

Dear all, welcome back to a new week. We hope you've had a great weekend. 

The aim this week is to discuss convolutional neural networks (CNNs), with the basic mathematics, which parameters we need to deal with and how we can implement CNNs using either Tensorflow/Keras and/or PyTorch. The lecture notes this week contain examples thereof. These examples can for example be used in project 3 if you to plan to use CNNs. Rashcka's text contains a good documentation on how to use PyTorch for both NNs, CNNs and recurrent neural networks (topic next week). 

These week there are no exercises, we will focus only on work on project 2. If you not yet received feedback on project 1, it should be there by the end of the day today, please apologize the delay to those who have not yet received feedback on p1.

This week our plans are as follows:

Material for the lecture on Monday November 3, 2025.

Lecture notes this week: Convolutional Neural Networks, codes and examples (TensorFlow and Pytorch implementations), see jupyter-notebook at  https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb

Readings and Videos: For a more in depth discussion on CNNs we recommend Goodfellow et al chapters 9. See also chapter 11 and 12 on practicalities and applications

Reading suggestions for implementation of CNNs, see Raschka et al chapters 14-15 at https://github.com/rasbt/machine-learning-book.

 Video on Deep Learning at https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

Lab sessions on Tuesday and Wednesday.

Discussion of and work on project 2, no exercises this week, only project work

best wishes to you all,

Morten et al