Python 3 code for my new book series Probabilistic Machine Learning. This is work in progress, so expect 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):
