v7.0.1

Small fixes compared to previous version 7.0.0

• remove dependency on codegen and ST4, to ease the library usage since it was used on code generation anyway
• surface on an interface some methods from TabularData

7.0.0

Major release with production ready implementation of multidimensional arrays, autodifferentiable tensor calculus and basic layers for neural networks.

6.1.0

Small bug fixes and refactories on tensor api

6.0.0

This release brings tensors as implementation for linear algebra and nd-arrays. Most of the algorithms were moved towards tensors.
It also brings fixes, refactored and covered new features and a cleaner API.

5.1.0

Bug fix release.

5.0.0

- update readme for 5.0.0

- prepare for release 5.0.0

v4.0.0

- refactor capabilities

Cleaner interfaces

• cleaner interfaces for machine learning base objects
• improved printable objects
• stable api for model evaluation

Stabilized API and systematic production code

This release marks the stabilization of the API. The new release marks also a continuous effort to cover with tests and make the non-experimental code production ready. Next minor releases will build on this one to increase to production quality code.

bug fixing

• improvements in xwilkinson
• renaming many data accessory for scala-like compatibility
• performance improvements in GBT and regression trees