Optuna
MLOps & Infrastructure
Overview
Optuna is an open-source hyperparameter optimization framework for machine learning that provides efficient search algorithms including Tree-structured Parzen Estimator (TPE), median pruner, and successive halving. It supports define-by-run API for flexible search spaces, pruning of unpromising trials, parallel optimization, and visualization. Optuna integrates with PyTorch, TensorFlow, and scikit-learn.
- Pricing model
- Free
- Deployment
- Self-hosted / on-premises, API / SDK
- Regions served
- Global
- Categories
- Free, MLOps & Infrastructure, Software & technology, Workflow orchestration, API / SDK, Self-hosted / on-premises, Predictive / classical ML, Functional application
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Deployment options
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- optuna.org
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
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