{"id":15026968,"url":"https://github.com/prml/prmlt","last_synced_at":"2025-05-14T13:09:07.794Z","repository":{"id":4603503,"uuid":"5746658","full_name":"PRML/PRMLT","owner":"PRML","description":"Matlab code of machine learning algorithms in book PRML","archived":false,"fork":false,"pushed_at":"2020-03-04T13:50:30.000Z","size":506,"stargazers_count":6123,"open_issues_count":0,"forks_count":2159,"subscribers_count":403,"default_branch":"master","last_synced_at":"2025-04-11T18:21:41.357Z","etag":null,"topics":["algorithms","machine-learning","machine-learning-algorithms","matlab","prml"],"latest_commit_sha":null,"homepage":"http://prml.github.io/","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/PRML.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2012-09-10T08:19:18.000Z","updated_at":"2025-04-08T09:27:22.000Z","dependencies_parsed_at":"2022-07-11T05:16:49.345Z","dependency_job_id":null,"html_url":"https://github.com/PRML/PRMLT","commit_stats":null,"previous_names":[],"tags_count":20,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PRML%2FPRMLT","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PRML%2FPRMLT/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PRML%2FPRMLT/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PRML%2FPRMLT/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/PRML","download_url":"https://codeload.github.com/PRML/PRMLT/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254149976,"owners_count":22022852,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithms","machine-learning","machine-learning-algorithms","matlab","prml"],"created_at":"2024-09-24T20:05:31.041Z","updated_at":"2025-05-14T13:09:02.781Z","avatar_url":"https://github.com/PRML.png","language":"MATLAB","readme":"Introduction\n-------\nThis Matlab package implements machine learning algorithms described in the great textbook:\nPattern Recognition and Machine Learning by C. Bishop ([PRML](http://research.microsoft.com/en-us/um/people/cmbishop/prml/)).\n\nIt is written purely in Matlab language. It is self-contained. There is no external dependency.\n\nNote: this package requires Matlab **R2016b** or latter, since it utilizes a new Matlab syntax called [Implicit expansion](https://cn.mathworks.com/help/matlab/release-notes.html?rntext=implicit+expansion\u0026startrelease=R2016b\u0026endrelease=R2016b\u0026groupby=release\u0026sortby=descending) (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data).\n\nDesign Goal\n-------\n* Succinct: The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted.\n* Efficient: Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans).\n* Robust: Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry\\PD, etc.\n* Readable: The code is heavily commented. Corresponding formulas in PRML are annoted. Symbols are in sync with the book.\n* Practical: The package is not only readable, but also meant to be easily used and modified to facilitate ML research. Many functions in this package are already widely used (see [Matlab file exchange](http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A49739)).\n\nInstallation\n-------\n1. Download the package to a local folder (e.g. ~/PRMLT/) by running: \n```console\ngit clone https://github.com/PRML/PRMLT.git\n```\n2. Run Matlab and navigate to the folder (~/PRMLT/), then run the init.m script.\n\n3. Run some demos in ~/PRMLT/demo folder. Enjoy!\n\nFeedBack\n-------\nIf you find any bug or have any suggestion, please do file issues. I am graceful for any feedback and will do my best to improve this package.\n\nLicense\n-------\nReleased under MIT license\n\nContact\n-------\nsth4nth at gmail dot com\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprml%2Fprmlt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprml%2Fprmlt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprml%2Fprmlt/lists"}