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R Deep Learning Cookbook : Powerful, Independent Recipes to Build Deep Learning Models in Different Application Areas Using R Libraries by Mark Hodnett, Joshua F. Wiley is a nonfiction available to read on EtoBox.

What is R Deep Learning Cookbook : Powerful, Independent Recipes to Build Deep Learning Models in Different Application Areas Using R Libraries about?

Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for computer vision and text Apply deep learning techniques in cloud for large-scale processing Build, train, and optimize neural network models on a range of datasets Book Description Deep learning is a powerful subset of machine learning that is very successful in domains such as computer vision and natural language processing (NLP). This second edition of R Deep Learning Essentials will open the gates for you to enter the world of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep learning and teach you to build a neural network model from scratch. As you make your way through the book, you will explore deep learning libraries, such as Keras, MXNet, and TensorFlow, and create interesting deep learning models for a variety of tasks and problems, including structured data, computer vision, text data, anomaly detection, and recommendation systems. You'll cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale dee

Who reads R Deep Learning Cookbook : Powerful, Independent Recipes to Build Deep Learning Models in Different Application Areas Using R Libraries?

Author

Mark Hodnett, Joshua F. Wiley

Publisher

Packt Publishing; Packt Publishing - ebooks Account

Published

2018

Language

EN

ISBN

9781787127111

Category

nonfiction

Subjects

Computer Science, Science, Mathematics