Plans for third week, February 3-7

Dear all and welcome back to FYS5429/FYS9429. We hope the week has started the best possible way.

The aim this week is to wrap up the review of neural networks we started last week, with a discussion of codes. 

Thereafter we start with CNNs and discuss their mathematics and how to implement CNNs ourselves, or using Tensorflow/PyTorch. We will continue with CNNs next week as well before we move over to RNNs. 

Also, this week we will have presentations of possible project ideas from you (5 min approx, 1-3 slides) towards the end of the second lecture and the first hour of the lab session.  Please send me a final confirmation by the end of Wednesday (Feb 5) if you wish to present and I will set up a schedule for tomorrow. And if you have a short title (and perhaps spme slides), even better.

You will also find examples of several projects from last year, see https://github.com/CompPhysics/AdvancedMachineLearning/tree/main/doc/Projects/ProjectExamples

The notes this week are best viewed as a jupyter-notebook, see https://github.com/CompPhysics/AdvancedMachineLearning/blob/main/doc/pub/week3/ipynb/week3.ipynb

The plan is this week is thus

Overview of third week

1. Short reminder of possible projects

2. Review of neural networks with codes and examples (continuation from last week)

3. Start discussion of Convolutional Neural Networks (CNNs)

4. Presentation of project ideas, towards end of second lecture and first lab session.

Reading recommendations

1. Rashkca et al., chapters 11-13 for NNs and chapter 14 for CNNs, jupyter-notebook sent separately, from GitHub

2. Goodfellow et al, chapter 6 and 7 contain most of the neural network background. For CNNs see chapter 9.

If something is unclear, please do not hesitate to get in touch.

Best wishes to you all,

Edvin and Morten