# PRML/PRMLT

Matlab code of machine learning algorithms in book PRML

Repository: https://github.com/PRML/PRMLT
Canonical: https://ross.abutalabs.com/products/prmlt
Homepage: http://prml.github.io/
Language: MATLAB
License: MIT
License Family: permissive
Topics: matlab, machine-learning, prml, algorithms, machine-learning-algorithms
Last push: 2020-03-04T13:50:30+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 5105, "days_push": 2373, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6201, forks 2126 (observed 2026-08-28T04:09:39.831680+00:00)

## What it is
A self-contained MATLAB toolbox implementing the machine learning algorithms from Bishop's textbook 'Pattern Recognition and Machine Learning' (PRML). The code is compact, heavily commented with references to the book's formulas, and designed for readability and research use.

## Use cases
- implement PRML book algorithms in MATLAB
- learn machine learning algorithms alongside the Bishop textbook
- find a fast MATLAB kmeans or EM implementation
- study numerically stable implementations of Bayesian inference
- use compact ML code for research prototyping

## When to choose
- you are studying the PRML textbook and want matching code
- you work in MATLAB and need readable, dependency-free ML algorithm implementations
- you need efficient, numerically robust MATLAB routines for research

## When to avoid
- you need production-grade ML tooling in Python or another language
- you require deep learning or GPU acceleration
- you don't have a MATLAB license or the Statistics/Image Processing toolboxes

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, data-science, math
- domain: machine-learning, data-science, education
- platform: windows
- tags: prml, textbook-companion, bayesian, pattern-recognition, matlab-toolbox, algorithms, matlab, macos, linux

## Member repositories
- PRML/PRMLT (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:39.831680+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:47:20.225302+00:00, confidence not recorded.
  - readme: https://github.com/PRML/PRMLT (fetched 2026-08-28T04:09:39.831680+00:00, sha cee245062c33)
  - homepage: http://prml.github.io/ (fetched 2026-08-29T08:43:46.849614+00:00, sha 7379a3bbf713)
- Data as of 2026-08-30T08:39:29.467469+00:00.