A library for supervised trainining of parameterized, regression and classification models
Design Goals
- Changing model representation, cost function and optimization algorithm independently from each other
- Generics: Not commiting to a particular datastructure for inputs, targets etc.
- If the design goals above can only be achieved by sacrificing performance, so be it
Current State
Just starting to get the traits right, by continously trying new use cases and implementing the learning algorithms. If you are looking for more mature rust libraries in the domain of ML you might want to check out:
Documentation
Thanks to the folks of docs.rs for building and hosting the documentation!
Contributing
Want to help out? Just create an issue, pull request or contact markus.klein@blue-yonder.com