Hyperas

Simple wrapper for hyperparameter optimization in Python.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is Hyperas?

Hyperas is a simple and convenient tool for optimizing hyperparameters of machine learning models. It wraps around Keras to provide an easy-to-use interface for tuning parameters, making it easier to improve model performance without manual trial and error.

Key differentiator

Hyperas stands out for its simplicity and ease of integration with Keras, making it an accessible choice for optimizing machine learning models without extensive setup or configuration.

Capability profile

Strength Radar

Simple integrati…Uses a genetic a…Easy-to-use API …

Honest assessment

Strengths & Weaknesses

↑ Strengths

Simple integration with Keras models for hyperparameter tuning.

Uses a genetic algorithm to optimize hyperparameters efficiently.

Easy-to-use API for defining search spaces and optimization objectives.

Fit analysis

Who is it for?

✓ Best for

Developers working with Keras who need to optimize hyperparameters without complex setup.

Projects where manual hyperparameter tuning is too time-consuming or impractical.

✕ Not a fit for

Users requiring real-time hyperparameter optimization in production environments.

Scenarios where the computational cost of genetic algorithms outweighs benefits.

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with Hyperas

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →