{"data":{"slug":"blobcity-autoai","name":"autoai","tagline":"Python based framework for Automatic AI enabling model search, hyper-parameter tuning and Jupyter Notebook code generation","github_url":"https://github.com/blobcity/autoai","owner":"blobcity","repo":"autoai","owner_avatar_url":"https://avatars.githubusercontent.com/u/3654980?v=4","primary_language":"Python","stars":186,"forks":46,"topics":["ai","autoai","automl","codegen","deep-learning","machine-learning","ml","python"],"archived":false,"github_pushed_at":"2025-03-25T01:40:10+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/blobcity-autoai","markdown_url":"https://www.graphcanon.com/tools/blobcity-autoai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/blobcity-autoai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=blobcity-autoai","description":"Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.","homepage_url":null,"license":"Apache-2.0","open_issues":9,"watchers":5,"ai_summary":"BlobCity's AutoAI supports automated machine learning workflows for regression and classification tasks over numerical data. It provides high-quality Python code generation in the form of Jupyter Notebooks.","readme_excerpt":"# Getting Started\n``` shell\npip install blobcity\n```\n\n``` Python\nimport blobcity as bc\nmodel = bc.train(file=\"data.csv\", target=\"Y_column\")\nmodel.spill(\"my_code.py\")\n```\n`Y_column` is the name of the target column. The column must be present within the data provided. \n\nAutomatic inference of Regression / Classification is supported by the framework.\n\nData input formats supported include:\n1. Local CSV / XLSX file\n2. URL to a CSV / XLSX file\n3. Pandas DataFrame \n\n``` Python\nmodel = bc.train(file=\"data.csv\", target=\"Y_column\") #local file\n```\n\n``` Python\nmodel = bc.train(file=\"https://example.com/data.csv\", target=\"Y_column\") #url\n```\n\n``` Python\nmodel = bc.train(df=my_df, target=\"Y_column\") #DataFrame\n```","github_created_at":"2021-08-31T12:15:41+00:00","created_at":"2026-07-11T23:32:41.236326+00:00","updated_at":"2026-08-04T00:02:00.643678+00:00","categories":[{"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":"ai","name":"ai"},{"slug":"autoai","name":"autoai"},{"slug":"automl","name":"automl"},{"slug":"codegen","name":"codegen"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"ml","name":"ml"},{"slug":"python","name":"python"}],"trust":{"provenance":{"is_fork":false,"github_id":401691119,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-04T00:01:59.898Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":496,"last_release_at":"2021-11-17T19:44:37Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":12,"high_count":0,"last_scan_at":"2026-07-11T23:32:44.293Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-04T00:02:00.358Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-04T00:02:00.358Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-04T00:02:00.358Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Use AutoAI when you need a tool that can handle both regression and classification tasks specifically over numerical datasets.","Choose this if your workflow requires Python-based high-quality Jupyter Notebook code generation from experimental models."],"when_not_to_use":["Avoid using AutoAI if your dataset includes non-numerical data exclusively as the framework is tailored for numerical data processing.","Do not use if generating model training scripts in formats other than Jupyter Notebooks is required, as this tool only supports Python code output within a Jupyter format."],"source":"enrich:decision_facts","observed_at":"2026-07-17T03:05:20.499Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Python based framework for automated machine learning focused on numerical data, providing model search, hyper-parameter tuning, and Jupyter Notebook code generation."}]}}