{"id":23042286,"url":"https://github.com/chuvalniy/tulia","last_synced_at":"2026-05-09T14:35:05.660Z","repository":{"id":209324537,"uuid":"713079822","full_name":"chuvalniy/Tulia","owner":"chuvalniy","description":"Contains self-implemented Machine Learning algorithms using only numpy.","archived":false,"fork":false,"pushed_at":"2024-02-13T13:53:59.000Z","size":3488,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-08T15:17:34.412Z","etag":null,"topics":["boosting","from-scratch","knn","learning","logistic-regression","machine","ml","numpy","python","random-forest","regression","sklearn","testing","xgboost"],"latest_commit_sha":null,"homepage":"","language":"Python","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/chuvalniy.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}},"created_at":"2023-11-01T19:50:00.000Z","updated_at":"2024-01-28T11:58:24.000Z","dependencies_parsed_at":"2024-02-06T15:02:30.341Z","dependency_job_id":null,"html_url":"https://github.com/chuvalniy/Tulia","commit_stats":null,"previous_names":["chuvalniy/ml-models","chuvalniy/tulia"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chuvalniy%2FTulia","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chuvalniy%2FTulia/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chuvalniy%2FTulia/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chuvalniy%2FTulia/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/chuvalniy","download_url":"https://codeload.github.com/chuvalniy/Tulia/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246916762,"owners_count":20854514,"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":["boosting","from-scratch","knn","learning","logistic-regression","machine","ml","numpy","python","random-forest","regression","sklearn","testing","xgboost"],"created_at":"2024-12-15T20:23:59.379Z","updated_at":"2026-05-09T14:35:00.622Z","avatar_url":"https://github.com/chuvalniy.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n![logo](/docs/logo.png)\n\nTulia: a comprehensive machine learning project entirely from scratch, utilizing the power of Python and numpy.\n\n\u003c/div\u003e\n\n## Features\n\n### Simplicity\n\nBy encapsulating both the training and predicting logic within just a couple of classes, complexity is greatly reduced compared to popular frameworks that heavily rely on abstraction.\nMoreover, the library provided here offers a streamlined approach by maintaining only essential parameters in the model class. \n\n### Familiar approach\n\nThis library uses sklearn API to build the codebase. \n\n## Example usage\n\n```python\nfrom src.linear import LinearRegression\n\nX_train, X_test, y_train, y_test = ...\n\nlr = LinearRegression(n_steps=10_000, learning_rate=1e-4)\nlr.fit(X_train, y_train)\n\ny_pred = lr.predict(X_test)\n\nmse = mean_squared_error(y_pred, y_test)  # Here mean_squared_error() is a pseudocode.\n```\n\n## Installation\n\n\n### To use in code\n\n```sh\npip install tulia\n```\n\n### Download a whole library\n\n```sh\ngit clone https://github.com/chuvalniy/Tulia.git\npip install -r requirements.txt\n```\n\n## Testing\n\nEvery machine learning model is provided with unit test that verifies correctness of fit and predict methods.\n\nExecute the following command in your project directory to run the tests.\n\n```python\npytest -v\n```\n\n## Demonstration\n\nThis [demo](/demos) folder contains jupyter-notebooks that compare scikit-learn and Tulia performance.\n\n## License\n[MIT License](LICENSE)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchuvalniy%2Ftulia","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchuvalniy%2Ftulia","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchuvalniy%2Ftulia/lists"}