{"id":21316146,"url":"https://github.com/jnlandu/base_ml_algo","last_synced_at":"2025-03-15T21:27:59.308Z","repository":{"id":227332503,"uuid":"771110997","full_name":"jnlandu/base_ml_algo","owner":"jnlandu","description":"Implementation of the Basic Machine Learning Algorithms","archived":false,"fork":false,"pushed_at":"2024-03-27T02:09:36.000Z","size":27,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-22T10:36:39.138Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jnlandu.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-03-12T17:50:54.000Z","updated_at":"2024-03-12T18:32:16.000Z","dependencies_parsed_at":"2024-03-27T03:24:32.110Z","dependency_job_id":null,"html_url":"https://github.com/jnlandu/base_ml_algo","commit_stats":null,"previous_names":["jnlandu/base_ml_algo"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jnlandu%2Fbase_ml_algo","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jnlandu%2Fbase_ml_algo/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jnlandu%2Fbase_ml_algo/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jnlandu%2Fbase_ml_algo/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jnlandu","download_url":"https://codeload.github.com/jnlandu/base_ml_algo/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243791875,"owners_count":20348532,"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":[],"created_at":"2024-11-21T18:29:58.974Z","updated_at":"2025-03-15T21:27:59.286Z","avatar_url":"https://github.com/jnlandu.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# base_ml_algo: \n\nDeveloping version of the implementation of basic machine learning algorithms taught/discussed in class at the AIMS AMMI program (visit https://aimsammi.org/)\n\n\n### Short details\n\nThis repository contains assignmemts, tests, quizes, and projects, that we did/will be doing at  the AIMS AMMI program. For the actual version, no much is done althought some a few works are already uploaded, notaby the implementation:\n* gradient descent method and its variants: Mini-Bacth GD  and Stochastic GD.\n* logistic regression, implementaion from scratch. The details about the dataset used will be given later.\n* linear regression, likewise, details for the the datasets will be discussed later.\nMost of those codes are written in python and use several packages libraies such as `numpy`, `pandas`,`pytorch`, etc.\n\n### Changes from now to March 31, 2024\nWe aim at to:\n* improve the code just uploaded, broaden it and include more features that have not appeared so far.\n* improve also the readability of the codes.\n* add related (short courses/short summary) of each concepts and/or techniques that have been used so far.\n* have the same codes but written in `R` (or `Julia`).\n* add collaboration, where needed.\n\n### Datasets\nFor  most of the present codes, we use the dataset provided by an appropriate library/package. For instance for the logistic implementation, the wide-known dataset `iris` from  `sklearn` was used to test our codes.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjnlandu%2Fbase_ml_algo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjnlandu%2Fbase_ml_algo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjnlandu%2Fbase_ml_algo/lists"}