Python 3 code for my new book series Probabilistic Machine Learning. This is work in progress, so expect very rough edges.
The scripts directory contains python files to generate individual figures from vol 1 and vol 2 of the book.
To manually execute an individual script from the command line,
follow this example:
cd pyprobml
python3 scripts/softmax_plot.py
This will save files to the pyprobml/figures directory.
To browse the code using VScode instead of the gihub file viewer, you can just replace https://github.com/probml/pyprobml/tree/master/scripts with https://github1s.com/probml/pyprobml/tree/master/scripts (see this tweet). The output should look like this:
The notebooks directory contains various examples that illustrate concepts and/or generate figures from vol 1 and vol 2 of the book.
In addition, we automatically combine all the figure scripts into a single notebook per chapter.
These are stored here.
When you open a notebook, there will be a button at the top that says 'Open in colab'. If you click on this, it will start a virtual machine (VM) instance on Google Cloud Platform (GCP), running Colab. This has most of the libraries you will need (e.g., scikit-learn, JAX) pre-installed, and gives you access to a free GPU. See this tutorial for details on how to use Colab.
See this guide for how to contribute code.
I would like to thank the following people for contributing to the code (list autogenerated from this page):
