Keras Tuner

Overview

A library for automating hyperparameter search in Keras models. It integrates with the Keras workflow and supports multiple search algorithms like Random Search and Bayesian Optimization. The library helps identify optimal hyperparameter configurations for improved model performance.

Best for

Best for
Developers using Keras who need automated hyperparameter optimization

Use cases

• Tuning learning rates and layer sizes for Keras neural networks
• Searching over hyperparameter spaces to find best validation metrics
• Automating hyperparameter optimization in Keras model training pipelines

Notes

A library for automating hyperparameter search in Keras models. It integrates with the Keras workflow and supports multiple search algorithms like Random Search and Bayesian Optimization. The library helps identify optimal hyperparameter configurations for improved model performance.

2,924 stars on GitHub. Last updated 2025-12-01. Licensed Apache-2.0.

Use cases

• Tuning learning rates and layer sizes for Keras neural networks
• Searching over hyperparameter spaces to find best validation metrics
• Automating hyperparameter optimization in Keras model training pipelines

Pros

• Seamless integration with Keras and TensorFlow
• Multiple built-in search algorithms
• Open source with an active community

Cons

• Limited to Keras and TensorFlow models only
• Hyperparameter search can be computationally intensive
• Not a general-purpose tuning tool for other frameworks

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