{"data":{"slug":"microsoft-flaml","name":"FLAML","tagline":"A fast library for AutoML and tuning","github_url":"https://github.com/microsoft/FLAML","owner":"microsoft","repo":"FLAML","owner_avatar_url":"https://avatars.githubusercontent.com/u/6154722?v=4","primary_language":"Jupyter Notebook","stars":4401,"forks":569,"topics":["automated-machine-learning","automl","classification","data-science","deep-learning","finetuning","hyperparam","hyperparameter-optimization","jupyter-notebook","machine-learning","natural-language-generation","natural-language-processing","python","random-forest","regression","scikit-learn","tabular-data","timeseries-forecasting","tuning"],"archived":false,"github_pushed_at":"2026-10-01T04:18:52+00:00","maintenance_label":"Very active","stars_delta_30d":16,"url":"https://www.graphcanon.com/tools/microsoft-flaml","markdown_url":"https://www.graphcanon.com/tools/microsoft-flaml.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/microsoft-flaml","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=microsoft-flaml","description":"A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.","homepage_url":"https://microsoft.github.io/FLAML/","license":"MIT","open_issues":180,"watchers":53,"ai_summary":"FLAML is a Python-based automated machine learning framework that simplifies hyperparameter optimization and model tuning for various tasks including classification, regression, natural language processing, and time-series forecasting.","readme_excerpt":"## Installation\n\nThe latest version of FLAML requires **Python >= 3.10 and < 3.14**. While other Python versions may work for core components, full model support is not guaranteed. FLAML can be installed via `pip`:\n\n```bash\npip install flaml\n```\n\nMinimal dependencies are installed without extra options. You can install extra options based on the feature you need. For example, use the following to install the dependencies needed by the [`automl`](https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML) module.\n\n```bash\npip install \"flaml[automl]\"\n```\n\nFind more options in [Installation](https://microsoft.github.io/FLAML/docs/Installation).\nEach of the [`notebook examples`](https://github.com/microsoft/FLAML/tree/main/notebook) may require a specific option to be installed.","github_created_at":"2020-08-20T20:46:11+00:00","created_at":"2026-07-11T23:34:08.286859+00:00","updated_at":"2026-10-02T06:00:06.860996+00:00","categories":[{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"automated-machine-learning","name":"automated-machine-learning"},{"slug":"classification","name":"classification"},{"slug":"data-science","name":"data-science"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"finetuning","name":"finetuning"},{"slug":"hyperparam","name":"hyperparam"},{"slug":"natural-language-processing","name":"natural language processing"},{"slug":"python","name":"python"}],"trust":{"provenance":{"is_fork":false,"github_id":289107293,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-10-02T06:00:05.940Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":1,"days_since_push":1,"last_release_at":"2026-09-18T05:31:39Z","stars_delta_30d":16,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:34:17.178Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-10-02T06:00:06.435Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-10-02T06:00:06.435Z","managed_saas":false},"languages":{"value":["jupyter notebook","python"],"source":"github.language+pyproject.toml","observed_at":"2026-10-02T06:00:06.435Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-10-02T06:00:06.435Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-10-02T06:00:06.435Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When working with Python >= 3.10 and < 3.14 to ensure full support of all models in FLAML.","For projects that demand high efficiency in model tuning and where the dataset involves classification, regression, or natural language processing tasks.","If you are interested in time-series forecasting and need an AutoML tool optimized for Python-based analysis without needing extensive manual hyperparameter adjustments."],"when_not_to_use":["When your project is restricted to using Python versions below 3.10 or equal to and above 3.14, as FLAML's full feature support may not be available.","If the scope of work does not include AutoML tasks such as hyperparameter optimization or model selection for classification, regression, NLP, or time-series forecasting.","For users who need cross-language compatibility beyond Python and Jupyter Notebook environments; FLAML primarily supports Python-based operations."],"source":"enrich:decision_facts","observed_at":"2026-07-17T06:11:46.976Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"FLAML streamlines AutoML and tuning tasks with optimized algorithms for model selection and hyperparameter optimization across classification, regression, NLP, and time-series forecasting."}]}}