Python 3 code for my new book series Probabilistic Machine Learning. This is work in progress, so expect rough edges.
For some of the chapters in the book, there are accompanying Jupyter notebooks that cover some of the material in more detail. 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, which has most of the libraries you will need (e.g., scikit-learn, tensorflow 2, JAX) pre-installed. (For libraries that are non pre-installed, the notebooks have code to install them for you.) You can select 'GPU' from the 'Runtime' menu at the top of Colab to make things run faster.
See this link for a list of notebooks.
See this link for a list of notebooks.
Many of the figures in the book are generated by these scripts. To execute a script, cd (change directory) to the scripts folder, and then type 'python foo.py'. You can also run each script from inside a Python IDE (like Spyder). Many of the scripts create plots, which are saved to ../figures directory.