v2.0

Big changes!

• The Network wrapper has been completely rewritten from the ground up, fixing some major bugs. The wrapper is also a lot more flexible now, making it easier to integrate new components in the future without having to rewrite any internals.
• Validation testing also supported when using network wrapper.
• More flexible and accurate Accuracy/Loss reporting.
• Fixed bug with Dropout layers when trying to get inference from the model.
• Added new Loss functions and activation layers to support a larger variety of models like classification, linear regression, binary logistic regression.

v1.0

Includes several components to build Deep Neural Networks, as well as a wrapper to allow faster and easier prototyping in just a few lines of code.