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Pattern Recognition and Machine Learning

Matlab implementation of algorithms from C. Bishop's book on PRML.

Status
UnmaintainedNo commits in 2366 days.
Last checked
Checked · Oct 10, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

This package contains the Matlab implementation of the algorithms described in 'Pattern Recognition and Machine Learning' by Christopher M. Bishop, providing a comprehensive resource for researchers and practitioners working with machine learning techniques.

The only open-source implementation of PRML algorithms in Matlab, providing a valuable resource for educational and research purposes.

When it fits — and when it doesn’t

A good fit for

  • Academics looking to implement PRML algorithms for research or teaching

  • Students studying machine learning who need practical examples of the concepts from Bishop's book

  • Developers prototyping new machine learning models in Matlab

Look elsewhere if

  • Teams requiring real-time processing capabilities as this is a library-based solution

  • Projects that require integration with cloud services or APIs, as it is primarily designed for local use

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited language support due to reliance on MATLAB

    The package is implemented in MATLAB, which restricts its use to those who have access to and are proficient with MATLAB.

  2. 02

    Performance issues for large datasets

    MATLAB can be slower compared to compiled languages like C++ or Python with optimized libraries when processing large-scale data.

  3. 03

    Documentation is primarily based on the book and lacks standalone comprehensive guides

    Users need to refer to 'Pattern Recognition and Machine Learning' by Christopher M. Bishop for detailed explanations, which can be a barrier for those without access or familiarity with the material.

  4. 04

    No active development or updates

    As an implementation of algorithms from a specific book, there are no ongoing improvements or new features being added, potentially making it less suitable for cutting-edge research.

What it does well

  • Comprehensive implementation of PRML algorithms

  • Educational resource for machine learning techniques

  • Open-source and freely available

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

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