Deep Netts Core Pro 1.2 API

Packages 
Package Description
deepnetts.core
Core engine configuration and settings.
deepnetts.data
Data structures and collections to provide example data to build machine learning models, and utility methods for common data manipulation.
deepnetts.data.norm
Data normalization methods, used to scale data, in order to make them suitable for use by neural network.
deepnetts.eval
Evaluation procedures for machine learning models, used to estimate how good models are performing for a given data.
deepnetts.net
Neural network architectures with their corresponding builders.
deepnetts.net.layers
Neural network layers, which are main building blocks of a neural network.
deepnetts.net.layers.activation
Activation functions for neural network layers.
deepnetts.net.loss
Commonly used loss functions, which are used to calculate error during the training as a difference between predicted and target output.
deepnetts.net.train
Training algorithms and related utilities.
deepnetts.net.train.opt
Optimization methods used by training algorithm.
deepnetts.net.weights
Weights randomization techniques, used for initializing layer's internal parameters.
deepnetts.util
Various utility classes including Tensor, image operations, multithreading, exceptions etc.