Plans for the week of March 3-7

Dear all, welcome back to FYS5429/9429. Our plans this week are

1. Reminder on basics of recurrent neural networks (RNNs) from last week

2. We will discuss in depth the mathematics of RNNs as this serves as an input to the possibility of developing own codes. The last point this week is then to develop our own code.

3. Writing our own codes for RNNs

Reading recommendations:

a. Goodfellow, Bengio and Courville's chapter 10 from Deep Learning, see https://www.deeplearningbook.org/

b. Sebastian Rashcka et al, chapter 15, Machine learning with Sickit-Learn and PyTorch, see https://sebastianraschka.com/blog/2022/ml-pytorch-book.html

c. David Foster, Generative Deep Learning with TensorFlow, see chapter 5, see https://www.oreilly.com/library/view/generative-deep-learning/9781098134174/ch05.html

The last two books have codes for RNNs in PyTorch and TensorFlow/Keras.

The jupyter-notebook is at https://github.com/CompPhysics/AdvancedMachineLearning/blob/main/doc/pub/week7/ipynb/week7.ipynb

Best wishes,

Edvin and Morten