{"id":26305650,"url":"https://github.com/clarelgibson/machine-learning-specialization-r","last_synced_at":"2025-03-15T09:16:40.110Z","repository":{"id":280863688,"uuid":"943428476","full_name":"clarelgibson/machine-learning-specialization-r","owner":"clarelgibson","description":"Includes worked examples in R of the machine learning algorithms covered in the Stanford/DeepLearning Machine Learning Specialisation","archived":false,"fork":false,"pushed_at":"2025-03-05T17:43:56.000Z","size":5,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-05T18:42:37.870Z","etag":null,"topics":["classification-algorithms","linear-regression","logistic-regression","machine-learning","r","r-language"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc0-1.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/clarelgibson.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-05T17:34:41.000Z","updated_at":"2025-03-05T17:46:20.000Z","dependencies_parsed_at":"2025-03-05T18:42:40.776Z","dependency_job_id":"e7b349e5-7399-4e0a-a834-e19db66c8a87","html_url":"https://github.com/clarelgibson/machine-learning-specialization-r","commit_stats":null,"previous_names":["clarelgibson/machine-learning-specialization-r"],"tags_count":0,"template":false,"template_full_name":"clarelgibson/sdg-template","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clarelgibson%2Fmachine-learning-specialization-r","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clarelgibson%2Fmachine-learning-specialization-r/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clarelgibson%2Fmachine-learning-specialization-r/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clarelgibson%2Fmachine-learning-specialization-r/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/clarelgibson","download_url":"https://codeload.github.com/clarelgibson/machine-learning-specialization-r/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243707352,"owners_count":20334619,"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":["classification-algorithms","linear-regression","logistic-regression","machine-learning","r","r-language"],"created_at":"2025-03-15T09:16:39.610Z","updated_at":"2025-03-15T09:16:40.101Z","avatar_url":"https://github.com/clarelgibson.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning in R\n\nThis repository contains worked examples in R of the machine learning algorithms covered in Andrew Ng's [Machine Learning Specialization](https://www.coursera.org/specializations/machine-learning-introduction) available on [Coursera](https://www.coursera.org).\n\n![](/img/mls-banner.png)\n\n## Description\n\nIn February 2025 I enrolled into the Machine Learning Specialization on Coursera. The course is jointly offered by [Stanford](https://www.coursera.org/partners/stanford) and [DeepLearning.ai](https://www.coursera.org/partners/deeplearning-ai) and the principal instructor is Stanford professor [Andrew Ng](https://en.wikipedia.org/wiki/Andrew_Ng). It is a great introduction to some of the most commonly used machine learning algorithms. In order for me to fully understand all of the concepts taught in the course, I felt that I needed to work through my own examples. While the course is taught using python, I chose to use R for this exercise, both because it's a language I am more familiar with and because it forces me to think and write the code for myself, rather than copy the code used in the lectures. \n\n## Algorithms\n\n- [Linear regression](R/linear-regression.md)\n\n## Author\n\n-   [Clare Gibson](https://www.datatranslator.co.uk)\n\n## Licence\n\nThis project is licensed under the CC0 1.0 Universal licence. See the [LICENSE](./LICENSE) file for details.\n\n## Acknowledgements\n\n- [Machine Learning Specialization](https://www.coursera.org/specializations/machine-learning-introduction)\n- [Coursera](https://coursera.org)\n- [DeepLearning.ai](https://deeplearning.ai)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fclarelgibson%2Fmachine-learning-specialization-r","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fclarelgibson%2Fmachine-learning-specialization-r","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fclarelgibson%2Fmachine-learning-specialization-r/lists"}