Python 3 code to reproduce the figures in the books Probabilistic Machine Learning: An Introduction (aka "book 1") and Probabilistic Machine Learning: Advanced Topics (aka "book 2"). The code uses the standard Python libraries, such as numpy, scipy, matplotlib, sklearn, etc. Some of the code (especially in book 2) also uses JAX, and in some parts of book 1, we also use Tensorflow 2 and a little bit of Torch. See also probml-utils for some utility code that is shared across multiple notebooks.

Features

  • Python code for "Probabilistic Machine learning" book by Kevin Murphy
  • Run notebooks in colab
  • Documentation available
  • Examples available
  • Run the notebooks locally
  • Cloud computing

Project Samples

pyprobml Screenshot 1

Project Activity

See All Activity >

Categories

Machine Learning

License

MIT License

Follow pyprobml

pyprobml Web Site

Other Useful Business Software
Build Agents and Models on One Platform Icon
Build Agents and Models on One Platform

Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
Try It Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of pyprobml!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Registered

2024-08-01
Report inappropriate content