{"id":25308164,"url":"https://github.com/mstryoda/ml-from-scratch","last_synced_at":"2025-04-06T02:12:10.572Z","repository":{"id":275941455,"uuid":"927686504","full_name":"mstrYoda/ml-from-scratch","owner":"mstrYoda","description":"A comprehensive collection of practical machine learning examples using popular frameworks and libraries.","archived":false,"fork":false,"pushed_at":"2025-02-09T17:41:54.000Z","size":62,"stargazers_count":125,"open_issues_count":1,"forks_count":4,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-03-30T01:11:23.125Z","etag":null,"topics":["llm","machine-learning","matplotlib","numpy","pandas","python","pytorch","sklearn"],"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/mstrYoda.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":"2025-02-05T11:25:00.000Z","updated_at":"2025-03-27T11:09:21.000Z","dependencies_parsed_at":"2025-02-05T12:28:42.582Z","dependency_job_id":"325d21e5-4adc-456a-b88e-011bf850ae19","html_url":"https://github.com/mstrYoda/ml-from-scratch","commit_stats":null,"previous_names":["mstryoda/ml-from-scratch"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mstrYoda%2Fml-from-scratch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mstrYoda%2Fml-from-scratch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mstrYoda%2Fml-from-scratch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mstrYoda%2Fml-from-scratch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mstrYoda","download_url":"https://codeload.github.com/mstrYoda/ml-from-scratch/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247423515,"owners_count":20936626,"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":["llm","machine-learning","matplotlib","numpy","pandas","python","pytorch","sklearn"],"created_at":"2025-02-13T11:57:32.446Z","updated_at":"2025-04-06T02:12:10.554Z","avatar_url":"https://github.com/mstrYoda.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning Examples Collection\n\nA comprehensive collection of practical machine learning examples using popular frameworks and libraries. This repository serves as a learning resource and reference for both beginners and experienced practitioners.\n\n## Repository Structure\n\n### 1. NumPy Examples (`numpy_examples/`)\nFundamental numerical computing examples:\n- Array operations and manipulation\n- Broadcasting and vectorization\n- Linear algebra operations\n- Random number generation\n- Mathematical functions\n- Performance optimization\n- Memory management\n\n### 2. Matplotlib Examples (`matplotlib_examples/`)\nData visualization examples:\n- Basic plotting techniques\n- Advanced plot customization\n- Statistical visualizations\n- Interactive plots\n- 3D plotting\n- Animation\n- Custom styling\n- Multiple subplots\n\n### 3. Pandas Examples (`pandas_examples/`)\nExamples for data manipulation and analysis:\n- Data cleaning and preprocessing\n- Data analysis and grouping\n- Time series analysis\n- Data visualization\n- Advanced operations\n- Merging and joining\n- Performance optimization\n\n### 4. Scikit-learn Examples (`sklearn_examples/`)\nCollection of examples demonstrating classical machine learning techniques:\n- Basic classification and regression\n- Feature engineering and selection \n- Model evaluation and tuning\n- Ensemble methods\n- Clustering and dimensionality reduction\n- Time series analysis\n- Handling imbalanced data\n- Model deployment\n\n### 5. HuggingFace Examples (`huggingface_examples/`)\nExamples for working with transformer models and NLP tasks:\n- Model fine-tuning\n- Custom training loops\n- Advanced training techniques\n- Model evaluation and inference\n- Deployment strategies\n\n### 6. PyTorch Examples (`pytorch_examples/`)\nExamples showcasing deep learning with PyTorch:\n- Basic tensor operations\n- Neural network implementations\n- CNN architectures\n- Transfer learning\n- Custom datasets and dataloaders\n- GPU acceleration\n- Model optimization\n\n## Getting Started\n\n### Prerequisites\n- Python 3.8+\n- pip or conda for package management\n\n## Acknowledgments\n- Open source ML community\n- Framework and library developers\n- Dataset providers\n- Contributors and users\n\n## Contact\nFor questions and feedback:\n- Create an issue in the repository\n- Contact maintainers directly\n- Join our community discussions\n\n## Future Plans\n- Add more interactive visualizations\n- Include deep learning visualization examples\n- Add reinforcement learning examples\n- Expand deployment examples\n- Include MLOps examples\n- Add AutoML examples\n- Include more real-world case studies\n- Add GPU optimization examples","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmstryoda%2Fml-from-scratch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmstryoda%2Fml-from-scratch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmstryoda%2Fml-from-scratch/lists"}