Deep Netts Core Pro 3.0.0 API

Packages

Package	Description
deepnetts.automl	Support for automatically building deep learning models using hyper-parameter search.
deepnetts.core	Core engine configuration and settings and runtime properties.
deepnetts.data	Data structures to store example data used for building machine learning models.
deepnetts.data.norm	Data normalization methods, used to scale data to specific range, in order to make them suitable for use by a neural network.
deepnetts.eval	Evaluation procedures for machine learning models, used to estimate how good models are performing when given new data that (that was not used for training).
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.