{"id":30195810,"url":"https://github.com/kolosalai/automl_tutorial","last_synced_at":"2025-08-13T05:02:36.449Z","repository":{"id":294575241,"uuid":"982526599","full_name":"KolosalAI/automl_tutorial","owner":"KolosalAI","description":"Tutorial using Kolosal AutoML","archived":false,"fork":false,"pushed_at":"2025-08-06T13:58:30.000Z","size":1164,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-08-06T15:44:21.880Z","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/KolosalAI.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,"zenodo":null}},"created_at":"2025-05-13T02:53:17.000Z","updated_at":"2025-08-06T13:58:34.000Z","dependencies_parsed_at":"2025-05-21T04:33:27.083Z","dependency_job_id":"b5baeed1-9fca-4550-b3af-db82e7961512","html_url":"https://github.com/KolosalAI/automl_tutorial","commit_stats":null,"previous_names":["genta-technology/automl_tutorial","kolosalai/automl_tutorial"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/KolosalAI/automl_tutorial","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KolosalAI%2Fautoml_tutorial","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KolosalAI%2Fautoml_tutorial/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KolosalAI%2Fautoml_tutorial/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KolosalAI%2Fautoml_tutorial/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/KolosalAI","download_url":"https://codeload.github.com/KolosalAI/automl_tutorial/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KolosalAI%2Fautoml_tutorial/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270183606,"owners_count":24541341,"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","status":"online","status_checked_at":"2025-08-13T02:00:09.904Z","response_time":66,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":[],"created_at":"2025-08-13T05:01:18.572Z","updated_at":"2025-08-13T05:02:36.245Z","avatar_url":"https://github.com/KolosalAI.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"Here's the improved and corrected version of your **Kolosal AutoML Tutorial README**:\n\n---\n\n# Kolosal AutoML Tutorial\n\nThis repository demonstrates how to use **Kolosal AutoML** to train, evaluate, and explain a regression model using the California Housing dataset.\n\n## 🚀 What You'll Learn\n\n* How to load and prepare data\n* How to train a model using Kolosal AutoML\n* How to evaluate model performance\n* How to generate a performance report\n* How to generate model explainability insights\n\n## 📦 Getting Started\n\n### 1. Clone the Repository\n\n```bash\ngit clone https://github.com/Genta-Technology/automl_tutorial.git\ncd automl_tutorial\n```\n\n### 2. Set Up the Environment Using `uv`\n\n#### a. (Optional) Create a Virtual Environment\n\n```bash\npython -m venv venv\n# On Windows:\nvenv\\Scripts\\activate\n# On macOS/Linux:\nsource venv/bin/activate\n```\n\n#### b. Install `uv` and Sync Dependencies\n\nInstall `uv` (a faster pip replacement):\n\n```bash\npip install uv\n```\n\nThen install dependencies:\n\n```bash\nuv pip sync requirements.lock.txt\n```\n\n\u003e `uv` is a fast dependency manager that automatically uses `pyproject.toml` for locking and syncing environments.\n\n### 3. Run the Jupyter Notebook\n\n```bash\njupyter notebook tutorial.ipynb\n```\n\n## 📁 Files\n\n* `tutorial.ipynb` – Main notebook tutorial\n* `requirements.lock.txt` – Locked dependency versions\n* `README.md` – This file\n\n## ✅ Requirements\n\n* Python 3.8+\n* Jupyter Notebook\n* Kolosal AutoML\n* scikit-learn\n* `uv` for dependency management\n\n## 📄 License\n\nThis project is licensed under the MIT License.\n\n---\n\nLet me know if you’d like to turn this into a `README.md` file directly or need a version tailored for `docs/`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkolosalai%2Fautoml_tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkolosalai%2Fautoml_tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkolosalai%2Fautoml_tutorial/lists"}