{"id":13705048,"url":"https://github.com/boralt/EmbeddedAI","last_synced_at":"2025-05-05T13:30:22.775Z","repository":{"id":74503380,"uuid":"96175207","full_name":"boralt/EmbeddedAI","owner":"boralt","description":"C++ AI library ","archived":false,"fork":false,"pushed_at":"2022-09-13T03:14:08.000Z","size":1514,"stargazers_count":13,"open_issues_count":0,"forks_count":0,"subscribers_count":6,"default_branch":"master","last_synced_at":"2024-08-03T22:14:16.764Z","etag":null,"topics":["ai","artificial-intelligence","bayesian","c-plus-plus"],"latest_commit_sha":null,"homepage":null,"language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/boralt.png","metadata":{"files":{"readme":"Readme.md","changelog":null,"contributing":null,"funding":null,"license":"COPYING","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2017-07-04T04:28:09.000Z","updated_at":"2024-02-22T19:59:19.000Z","dependencies_parsed_at":"2024-01-07T00:09:18.820Z","dependency_job_id":"a56868fb-589d-4af6-a9c3-3b16a4136533","html_url":"https://github.com/boralt/EmbeddedAI","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boralt%2FEmbeddedAI","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boralt%2FEmbeddedAI/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boralt%2FEmbeddedAI/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boralt%2FEmbeddedAI/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/boralt","download_url":"https://codeload.github.com/boralt/EmbeddedAI/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224448844,"owners_count":17313128,"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":["ai","artificial-intelligence","bayesian","c-plus-plus"],"created_at":"2024-08-02T22:00:30.680Z","updated_at":"2024-11-13T12:31:19.557Z","avatar_url":"https://github.com/boralt.png","language":"C++","readme":"# EmbeddedAI    \r\r*EmbededAI* is a library that provides elements of AI to C++ applications.\rDue to small footprint it is usable even for small embedded systems.\rInitial set of algorithms in this library is based on Bayesian approach to AI.\rThis library can dramatically simplify implementation of what otherwise \rwould be complicated custom programming of hard to implement and maintain logic. \rWith Bayesian approach the results are consistent with easily visualized model. \r\r# Methodology\r  1. Build Model\r\n  2. Apply sample/measurement\r\n  3. Query model for inference of non-directly observed variables\r\n  4. Query model for decisions based on maximum payoff/lowes loss\r\n\r![model](./docs/model.png)\r \r \r\r## Applications\r   * Based on observations determine probabilities of any individual cause or \r combination of causes \r   * Find the most likely explanations of any given observation (Minimum Probability of Error MPE)\r   * Find most likely values of certain causes given observation (Maximum Aposteriori Probability MAP)\r   * Find optimal sequence of decisions (actions) given costs (payoffs) \r     and observations performed prior to any action. \r\rDoxygen pages of Library Components can be viwed [here](https://rawgit.com/boralt/EmbeddedAI/master/api/html/classes.html)\r\r## API\r\rProject [Wiki](https://github.com/boralt/EmbeddedAI/wiki) contains brief API information. See doxygen pages [here](https://rawgit.com/boralt/EmbeddedAI/master/api/html/classes.html)\r\r\r## Examples\rSeveral test applications providing usage samples are available in ./tests \rdirectory and described in doxygen. Project wiki contains detailed walthrough\rof sample implementations.\r\r\r","funding_links":[],"categories":["Machine Learning \u0026 AI on MCU","微控制器 MCU 端"],"sub_categories":["USB","Awesome-Embedded Repository"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboralt%2FEmbeddedAI","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fboralt%2FEmbeddedAI","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboralt%2FEmbeddedAI/lists"}