{"id":18947607,"url":"https://github.com/elcaiseri/machine-learning-from-scratch","last_synced_at":"2026-03-10T06:30:55.676Z","repository":{"id":175022890,"uuid":"613035462","full_name":"elcaiseri/Machine-Learning-from-Scratch","owner":"elcaiseri","description":"Machine Learning using NumPy","archived":false,"fork":false,"pushed_at":"2023-07-27T15:36:34.000Z","size":16,"stargazers_count":7,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-07T11:35:34.662Z","etag":null,"topics":["knn","linear-regression","logistic-regression","machine-learning","mlp","naive-bayes","numpy"],"latest_commit_sha":null,"homepage":"","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/elcaiseri.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":"2023-03-12T17:46:36.000Z","updated_at":"2025-04-10T17:32:04.000Z","dependencies_parsed_at":null,"dependency_job_id":"52d6394b-2e8c-40cc-bff8-245dd27dac19","html_url":"https://github.com/elcaiseri/Machine-Learning-from-Scratch","commit_stats":null,"previous_names":["elcaiseri/machine-learning-from-scratch"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/elcaiseri/Machine-Learning-from-Scratch","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elcaiseri%2FMachine-Learning-from-Scratch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elcaiseri%2FMachine-Learning-from-Scratch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elcaiseri%2FMachine-Learning-from-Scratch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elcaiseri%2FMachine-Learning-from-Scratch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/elcaiseri","download_url":"https://codeload.github.com/elcaiseri/Machine-Learning-from-Scratch/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elcaiseri%2FMachine-Learning-from-Scratch/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30326891,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-10T05:25:20.737Z","status":"ssl_error","status_checked_at":"2026-03-10T05:25:17.430Z","response_time":106,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["knn","linear-regression","logistic-regression","machine-learning","mlp","naive-bayes","numpy"],"created_at":"2024-11-08T13:10:38.970Z","updated_at":"2026-03-10T06:30:55.647Z","avatar_url":"https://github.com/elcaiseri.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ccenter\u003e\n  \n\u003cimg src=\"https://www.python.org/static/community_logos/python-logo-master-v3-TM.png\" alt=\"Python\" width=\"50%\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/numpy/numpy/main/branding/logo/primary/numpylogo.svg\" alt=\"NumPy\" width=\"50%\"\u003e\n\n\u003c/center\u003e\n\nThis repository contains a collection of classic machine learning algorithms implemented from scratch using only the Python NumPy library.\n\n## Table of Contents\n- [About](#about)\n- [Algorithms](#algorithms)\n- [To-Do](#to-do)\n- [Usage](#usage)\n- [Contributing](#contributing)\n- [License](#license)\n\n## About\nMachine Learning from Scratch is a project aimed at deepening our understanding of fundamental machine learning algorithms. By implementing these algorithms using only the NumPy library, we gain insights into the underlying mathematical concepts and optimization techniques.\n\n## Algorithms\nCurrently, the following algorithms have been implemented:\n- k-Nearest Neighbors (knn.py)\n- Linear Regression (linearRegression.py)\n- Logistic Regression (logisticRegression.py)\n- Naive Bayes (naiveBayes.py)\n- Multi-Layer Perceptron (mlp.py)\n\nEach algorithm is self-contained in its respective Python file.\n\n## To-Do\n- Add comments to explain the equations used in each algorithm.\n- ~~Implement the Multi-Layer Perceptron (MLP) algorithm.~~\n\n## Usage\nYou can use these implementations to explore and experiment with the behavior of classic machine learning algorithms. To get started, follow these steps:\n1. Clone the repository: `git clone https://github.com/elcaiseri/Machine-Learning-from-Scratch.git`\n2. Install the required dependencies: `pip install -r requirements.txt`\n3. Open the Python files corresponding to the algorithm of interest.\n4. Run the Python scripts to observe the algorithm's behavior.\n\n## Contributing\nWe welcome contributions to improve existing implementations, add new algorithms, or fix issues. If you'd like to contribute, please follow the guidelines in [CONTRIBUTING.md](CONTRIBUTING.md).\n\n## License\nThis project is licensed under the [MIT License](LICENSE).\n\n---\n*If you find this project helpful or interesting, consider giving it a star! :star:*\n\n*© 2023 [elcaiseri](https://github.com/elcaiseri)*\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felcaiseri%2Fmachine-learning-from-scratch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Felcaiseri%2Fmachine-learning-from-scratch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felcaiseri%2Fmachine-learning-from-scratch/lists"}