A library for supervised training of parameterized, regression, and classification models
- Changing model representations, cost functions, and optimization algorithms independently of each other
- Generics: Not committing to a particular data structure for inputs, targets, etc.
- If the design goals above can only be achieved by sacrificing performance, so be it
Just starting to get the traits right, by continuously 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:
Thanks to the folks of docs.rs for building and hosting the documentation!
Want to help out? Just create an issue, pull request or contact [email protected]