{"id":25495541,"url":"https://github.com/xcollab/ml-algorithms-from-scratch","last_synced_at":"2025-04-10T02:42:05.136Z","repository":{"id":266231404,"uuid":"897760291","full_name":"codewithdark-git/ML-Algorithms-From-Scratch","owner":"codewithdark-git","description":"A comprehensive collection of machine learning algorithms implemented from scratch and using popular libraries, with detailed explanations and practical examples.","archived":false,"fork":false,"pushed_at":"2025-02-27T12:16:32.000Z","size":37222,"stargazers_count":26,"open_issues_count":0,"forks_count":12,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-31T18:46:11.526Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/codewithdark-git.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":"2024-12-03T07:34:01.000Z","updated_at":"2025-03-29T23:09:56.000Z","dependencies_parsed_at":"2024-12-03T08:34:59.146Z","dependency_job_id":"53f463d1-1608-4cf2-86ca-2fbe7668e269","html_url":"https://github.com/codewithdark-git/ML-Algorithms-From-Scratch","commit_stats":null,"previous_names":["codewithdark-git/ml-algorithms-from-scratch","xcollab/ml-algorithms-from-scratch"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codewithdark-git%2FML-Algorithms-From-Scratch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codewithdark-git%2FML-Algorithms-From-Scratch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codewithdark-git%2FML-Algorithms-From-Scratch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codewithdark-git%2FML-Algorithms-From-Scratch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/codewithdark-git","download_url":"https://codeload.github.com/codewithdark-git/ML-Algorithms-From-Scratch/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248144980,"owners_count":21055021,"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":"2025-02-19T00:37:21.752Z","updated_at":"2025-04-10T02:42:05.113Z","avatar_url":"https://github.com/codewithdark-git.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ML-Algorithms-From-Scratch\n\nA comprehensive collection of machine learning algorithms implemented both from scratch and using popular libraries. Each implementation includes detailed explanations, mathematical concepts, and practical examples.\n\n## 🎯 Project Goal\nThis repository aims to provide clear, well-documented implementations of machine learning algorithms to help understand their inner workings. Each algorithm is implemented twice:\n1. From scratch using NumPy (to understand the core concepts)\n2. Using popular libraries like scikit-learn (for practical applications)\n\n\n## 🗂️ Algorithms Included\n- Linear Regression\n  - Methods:\n    - Gradient Descent\n    - Normal Equation\n  - Simple Linear Regression\n  - Multiple Linear Regression\n  - Polynomial Regression\n- Gradient Descent\n  - Batch Gradient Descent\n  - Stochastic Gradient Descent\n- Neural Networks\n  - Neural Network from Scratch\n- Decision Tree\n- PINN (Physics Inform Neural Network)\n\n\n- More algorithms coming soon:\n  - Logistic Regression\n  - Support Vector Machines\n  - K-means Clustering\n  - Naive Bayes\n  - Dimensionality Reduction\n\n## 📚 Features\n- Detailed Jupyter notebooks with step-by-step explanations\n- Mathematical concepts and formulas\n- Visualizations of algorithm behavior\n- Performance comparisons\n- Real-world examples and use cases\n- Comprehensive documentation\n\n## 🛠️ Technologies Used\n- Python 3.8+\n- NumPy\n- Matplotlib\n- scikit-learn\n- Jupyter Notebook\n\n## 🚀 Getting Started\n1. Clone the repository\n2. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n3. Navigate to any algorithm folder\n4. Open the Jupyter notebooks to see implementations\n\n## 📖 Learning Path\nEach algorithm folder contains:\n- Theoretical explanation\n- Step-by-step implementation\n- Visualization of results\n- Practical examples\n- Performance evaluation\n\n## 🤝 Contributing\nContributions are welcome! Feel free to:\n- Add new algorithms\n- Improve existing implementations\n- Add more examples\n- Enhance documentation\n\n## 📝 License\nThis project is licensed under the MIT License - see the LICENSE file for details..\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxcollab%2Fml-algorithms-from-scratch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxcollab%2Fml-algorithms-from-scratch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxcollab%2Fml-algorithms-from-scratch/lists"}