DeepHyper is first and foremost a hyperparameter optimization (HPO) library. By leveraging this core HPO functionality, DeepHyper also provides neural architecture search, multi-fidelity and ensemble capabilities. With DeepHyper, users can easily perform these tasks on a single machine or distributed across multiple machines, making it ideal for use in a variety of environments.
The project is organized across different repositories:
deephyper: Main Python package.documentation: Documentation website.benchmark: Set of benchmarks to evaluate the performance.
