Information about notebooks: There are are a total of 20 notebooks that accompany the review. Most of these notebooks are new. However, others (mostly those based on the MNIST dataset) are modified versions of notebooks/tutorials developed by the makers of commonly used machine learning packages such as Keras, PyTorch, scikit learn, TensorFlow, as well as a new package Paysage for energy-based generative model maintained by Unlearn.AI. All the notebooks make generous use of code from these tutorials as well the rich ecosystem of publically available blog posts on Machine Learning by researchers, practioners, and students. We have included links to all relevant sources within each notebook. For full disclosure, we note that Unlearn.AI is affiliated with two of the authors Charles Fisher (founder) and Pankaj Mehta (scientific advisor).
The notebooks are named according to the convention NB_CXX-description.ipynb where CXX refers to the corresponding section in the review (e.g. a notebook for Section VII about Random Forests will have a name of the form NB_CVII-Random_Forests.ipynb).