Advanced Deep Learning with R

3.5 (2 reviews total)
By Bharatendra Rai
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  1. Section 1: Revisiting Deep Learning Basics

About this book

Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data. Advanced Deep Learning with R will help you understand popular deep learning architectures and their variants in R, along with providing real-life examples for them.

This deep learning book starts by covering the essential deep learning techniques and concepts for prediction and classification. You will learn about neural networks, deep learning architectures, and the fundamentals for implementing deep learning with R. The book will also take you through using important deep learning libraries such as Keras-R and TensorFlow-R to implement deep learning algorithms within applications. You will get up to speed with artificial neural networks, recurrent neural networks, convolutional neural networks, long short-term memory networks, and more using advanced examples. Later, you'll discover how to apply generative adversarial networks (GANs) to generate new images; autoencoder neural networks for image dimension reduction, image de-noising and image correction and transfer learning to prepare, define, train, and model a deep neural network.

By the end of this book, you will be ready to implement your knowledge and newly acquired skills for applying deep learning algorithms in R through real-world examples.

Publication date:
December 2019
Publisher
Packt
Pages
352
ISBN
9781789538779

 

Section 1: Revisiting Deep Learning Basics

This section contains a chapter that serves as an introduction to deep learning with R. It provides an overview of the process for developing deep networks and reviews popular deep learning techniques.

This section contains the following chapter:

  • Chapter 1, Revisiting Deep Learning Architecture and Techniques

About the Author

  • Bharatendra Rai

    Bharatendra Rai is a chairperson and professor of business analytics, and the director of the Master of Science in Technology Management program at the Charlton College of Business at UMass Dartmouth. He received a Ph.D. in industrial engineering from Wayne State University, Detroit. He received a master's in quality, reliability, and OR from Indian Statistical Institute, India. His current research interests include machine learning and deep learning applications. His deep learning lecture videos on YouTube are watched in over 198 countries. He has over 20 years of consulting and training experience in industries such as software, automotive, electronics, food, chemicals, and so on, in the areas of data science, machine learning, and supply chain management.

    Browse publications by this author

Latest Reviews

(2 reviews total)
O livro adquirido apresenta superficialidade de conteúdo teórico, alguns arquivos de download difere dos apresentados no texto, e além disso, alguns estão desorganizados.
This is such a book that I was waiting for long. 326 pages - not a big one! But I wanted to learn advanced level as deep as required in a moderated time. Got lots of pragmatic tips and tricks. Anyone may go through this book. I am sure it will be a perfect use of precious time.

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