Deep Learning with R Cookbook

Preface

Deep learning has taken a huge step in recent years with developments including generative adversarial networks (GANs), variational autoencoders, and deep reinforcement learning. This book serves as a reference guide in R 3.x that will help you implement deep learning techniques.

This book walks you through various deep learning techniques that you can implement in your applications using R 3.x. A unique set of recipes will help you solve regression, binomial classification, and multinomial classification problems, and explores hyper-parameter optimization in detail. You will also go through recipes that implement convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, sequence-to-sequence ...