gerdm/prml
This project contains Jupyter notebook implementations of algorithms from Bishop's Pattern Recognition and Machine Learning textbook.
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The repository provides Python implementations of algorithms and graph reproductions from the classic PRML textbook by Christopher Bishop. It covers topics including Bayesian statistics, linear regression, density estimation, mixture models, kernel methods, and other foundational machine learning techniques. The content is structured by chapter with exercises and demonstrations in Jupyter notebook format.
Frequently asked
- What is gerdm/prml?
- This project contains Jupyter notebook implementations of algorithms from Bishop's Pattern Recognition and Machine Learning textbook.
- Is prml open source?
- Yes — gerdm/prml is open source, released under the AGPL-3.0 license.
- What language is prml written in?
- gerdm/prml is primarily written in Jupyter Notebook.
- How popular is prml?
- gerdm/prml has 2.6k stars on GitHub.
- Where can I find prml?
- gerdm/prml is on GitHub at https://github.com/gerdm/prml.