Weekly update and plans for week41
Dear all. Thanks a million for heroic efforts with project 1.
Project 2 is now available and the first part builds on project 1 (it is a continuation of project 1) where you are going to replace your matrix inversion algorithm with a gradient descent algorithm for OLS and Ridge regression. Thereafter you will have to develop a neural network code for both regression and classification.
At the lab Wednesday we recommend thus to get started with implementing this. Last week we discussed various gradient methods as well as developing the back propagation algorithm.
This week we will discuss this algorithm and how to write our own feed forward neural network. This will serve as a useful starting point for project 2.
The topics this week are thus:
- Lab Wednesday: Work on project 2
- Lecture Thursday: Deep learning and Neural Networks
- Lecture Friday: Convolutional Neural Networks, basic elements
- Reading recommendations:
- See lecture notes for week 41 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
- For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications. See also Aurelien Geron's chapters 10-11 at https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf.
Best wishes to you all,
Morten et al