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Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Optuna ⭐ 9,572

A hyperparameter optimization framework

Polyaxon ⭐ 3,438

MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle

Optuna Examples ⭐ 538

Examples for https://github.com/optuna/optuna

Neuraxle ⭐ 533

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

Parallel Hyperparameter Tuning in Python

Propulate ⭐ 24

Propulate is an asynchronous evolutionary optimization algorithm and software package for global optimization and hyperparameter search on high-performance computers.

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