Welcome to apsis’s documentation!

A toolkit for hyperparameter optimization for machine learning algorithms.

Our goal is to provide a flexible, simple and scaleable approach - parallel, on clusters and/or on your own machine. Check out our usage tutorials to get started or the design pages to understand how apsis works.

Project State

We have reached the beta state now. Documentation is ready, test covergae is at 90%.

Scientific Project Description

If you want to learn more on the project and are interested in the theoretical background on hyperparameter optimization used in apsis you may want to check out the scientific project documentation.

Furthermore, a presentation slide deck is available at slideshare.

License

The project is licensed under the MIT license, see the License file on github.

Indices and tables