R Deep Learning Cookbook

What this book covers

Chapter 1, Getting Started, introduces different packages that are available for building deep learning models, such as TensorFlow, MXNet, and H2O. and how to set them up to be utilized later in the book.

Chapter 2, Deep Learning with R, introduces the basics of neural network and deep learning. This chapter covers multiple recipes for building a neural network models using multiple toolboxes in R.

Chapter 3, Convolution Neural Network, covers recipes on Convolution Neural Networks (CNN) through applications in image processing and classification.

Chapter 4, Data Representation Using Autoencoders, builds the foundation of autoencoder using multiple recipes and also covers the application in data compression and denoising. ...