{"data":{"slug":"determined-ai-determined","name":"determined","tagline":"An open-source machine learning platform for distributed training and resource management.","github_url":"https://github.com/determined-ai/determined","owner":"determined-ai","repo":"determined","owner_avatar_url":"https://avatars.githubusercontent.com/u/26636771?v=4","primary_language":"Go","stars":3227,"forks":373,"topics":["data-science","deep-learning","distributed-training","hyperparameter-optimization","hyperparameter-search","hyperparameter-tuning","keras","kubernetes","machine-learning","ml-infrastructure","ml-platform","mlops","pytorch","tensorflow"],"archived":false,"github_pushed_at":"2025-03-20T19:09:46+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/determined-ai-determined","markdown_url":"https://www.graphcanon.com/tools/determined-ai-determined.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/determined-ai-determined","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=determined-ai-determined","description":"Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.","homepage_url":"https://determined.ai","license":"Apache-2.0","open_issues":108,"watchers":76,"ai_summary":"Determined is an ML platform that streamlines distributed model training, includes hyperparameter tuning components, supports PyTorch and TensorFlow integration, and provides tools for experiment tracking and resource administration via CLI or deployment on Kubernetes, AWS, GCP, Slurm, or PBS.","readme_excerpt":"# Installation\n\nTo install the CLI:\n\n```bash\npip install determined\n```\n\nThen use `det deploy` to start the Determined cluster locally, or on cloud services like AWS and GCP.\n\nFor installation details, visit the the cluster deployment guide for your environment:\n\n- [Local (on-prem)](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/on-prem/overview.html)\n- [AWS](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/aws/overview.html)\n- [GCP](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/gcp/overview.html)\n- [Kubernetes](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/k8s/overview.html)\n- [Slurm/PBS](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/slurm/overview.html)","github_created_at":"2020-04-07T16:12:29+00:00","created_at":"2026-07-11T23:33:39.910295+00:00","updated_at":"2026-08-04T06:00:41.082875+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":"data-science","name":"data-science"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"distributed-training","name":"distributed-training"},{"slug":"hyperparameter-optimization","name":"hyperparameter-optimization"},{"slug":"ml-infrastructure","name":"ml-infrastructure"},{"slug":"pytorch","name":"pytorch"},{"slug":"tensorflow","name":"tensorflow"}],"trust":{"provenance":{"is_fork":false,"github_id":253846879,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-04T06:00:40.284Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":501,"last_release_at":"2025-03-19T23:12:44Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":39,"high_count":0,"last_scan_at":"2026-07-11T23:33:45.273Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-04T06:00:40.788Z"},"languages":{"value":["go","python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-04T06:00:40.788Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-04T06:00:40.788Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here."},"requirements":{"notes":["Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`."],"min_ram_gb":null,"requires_docker":false},"constraints":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"when_to_use":["You require a streamlined solution for distributed model training, particularly if you are working with PyTorch or TensorFlow frameworks.","Need advanced features for hyperparameter tuning and experiment tracking within your ML workflow.","Utilizing Kubernetes, AWS, GCP, Slurm, or PBS as part of your infrastructure setup."],"when_not_to_use":["Seeking a platform that supports more machine learning frameworks beyond PyTorch and TensorFlow.","Your current stack does not include any of the supported infrastructures like Kubernetes or cloud services where Determined can be deployed."],"source":"enrich:decision_facts","observed_at":"2026-07-17T05:24:55.172Z"},"constraint_facets":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here."},{"label":"Requirements","value":"Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`."},{"label":"Adopt for","value":"Determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications."},{"label":"License detail","value":"Apache-2.0"}]}}