{"id":20251732,"url":"https://github.com/jfmdev/simple_ml","last_synced_at":"2026-05-07T04:37:48.999Z","repository":{"id":84199954,"uuid":"250634876","full_name":"jfmdev/simple_ml","owner":"jfmdev","description":"Simple examples of Machine Learning notebooks","archived":false,"fork":false,"pushed_at":"2021-01-20T19:24:32.000Z","size":3589,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-05-28T07:03:12.378Z","etag":null,"topics":["artificial-intelligence","jupyter-notebook","kaggle","machine-learning","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jfmdev.png","metadata":{"files":{"readme":"readme.md","changelog":null,"contributing":null,"funding":null,"license":"license.txt","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":"2020-03-27T20:02:29.000Z","updated_at":"2023-06-07T14:42:01.000Z","dependencies_parsed_at":"2023-05-23T22:45:26.622Z","dependency_job_id":null,"html_url":"https://github.com/jfmdev/simple_ml","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jfmdev/simple_ml","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jfmdev%2Fsimple_ml","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jfmdev%2Fsimple_ml/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jfmdev%2Fsimple_ml/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jfmdev%2Fsimple_ml/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jfmdev","download_url":"https://codeload.github.com/jfmdev/simple_ml/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jfmdev%2Fsimple_ml/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271027687,"owners_count":24687082,"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","status":"online","status_checked_at":"2025-08-18T02:00:08.743Z","response_time":89,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["artificial-intelligence","jupyter-notebook","kaggle","machine-learning","python"],"created_at":"2024-11-14T10:12:33.072Z","updated_at":"2025-10-06T13:20:16.267Z","avatar_url":"https://github.com/jfmdev.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Simple ML\n\nThis repository contains examples of Jupyter notebooks and Python files that uses Machine Learning techniques to build simple models or agents.\n\n * The bots on `candy-cane` folder uses _reinforcement learning_ to solve a variant of the \"multi-armed bandit\" problem.\n * The notebook on `disaster` folder uses _natural language processing_ to predict if a Tweet is announcing an emergency.\n * The notebook on `houses` folder uses _linear regression_ and _ridge regression_ models to predict the sales prices of houses.\n * The notebook on `mushrooms` folder uses _descision tree_ and _random forest_ models to predict which mushrooms are edible and which are poisonous.\n * The bot on `rock-paper-scissors` folder uses _reinforcement learning_ to play the Rock Paper Scissors game.\n * The notebook on `santa-tour` folder uses _linear programming_ to find the best way to schedule tours to a site with capacity constraints. \n * The notebook on `titanic` folder uses _descision tree_ and _random forest_ models to predict which passengers survived the Titanic sink. \n\nLicense\n-------\n\nAll the code in this repository is free software; you can redistribute it and/or modify it under the terms of the Mozilla Public License v2.0.  \nYou should have received a copy of the MPL 2.0 along with this repository, otherwise you can obtain one at http://mozilla.org/MPL/2.0/.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjfmdev%2Fsimple_ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjfmdev%2Fsimple_ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjfmdev%2Fsimple_ml/lists"}