probml/pmtk3

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1569 stars · 784 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PMTK3 is a Matlab/Octave toolkit of probabilistic machine learning models and algorithms, created to accompany Kevin Murphy's textbook 'Machine Learning: a Probabilistic Perspective'. It provides reference implementations of regression, SVMs, Gaussian processes, graphical models, latent variable models, and Bayesian inference methods.

Use cases

• implement probabilistic machine learning models in matlab
• learn algorithms from the machine learning a probabilistic perspective textbook
• run bayesian inference examples like MCMC and variational bayes
• explore reference implementations of EM, HMMs, and graphical models
• reproduce textbook figures and exercises in octave

When to choose

• you are studying Murphy's textbook and want matching Matlab/Octave code
• you need readable reference implementations of classic probabilistic ML algorithms
• you work in Matlab or Octave and want a broad ML toolbox

When to avoid

• you need maintained software with bug fixes or new features
• you prefer Python - use the successor pyprobml instead
• you need production-grade performance or modern deep learning support

Facets

library · maturity abandoned

machine-learning data-science math machine-learning data-science education matlab octave bayesian-statistics graphical-models textbook-companion unmaintained algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="probml/pmtk3")