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R Deep Learning Cookbook

You're reading from   R Deep Learning Cookbook Solve complex neural net problems with TensorFlow, H2O and MXNet

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787121089
Length 288 pages
Edition 1st Edition
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Authors (2):
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Achyutuni Sri Krishna Rao Achyutuni Sri Krishna Rao
Author Profile Icon Achyutuni Sri Krishna Rao
Achyutuni Sri Krishna Rao
PKS Prakash PKS Prakash
Author Profile Icon PKS Prakash
PKS Prakash
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Deep Learning with R 3. Convolution Neural Network 4. Data Representation Using Autoencoders 5. Generative Models in Deep Learning 6. Recurrent Neural Networks 7. Reinforcement Learning 8. Application of Deep Learning in Text Mining 9. Application of Deep Learning to Signal processing 10. Transfer Learning

Preface

Deep learning is one of the most commonly discussed areas in machine learning due to its ability to model complex functions and learn through a variety of data sources and structures, such as cross-sectional data, sequential data, images, text, audio, and video. Also, R is one of the most popular languages used in the data science community. With the growth of deep learning, the relationship between R and deep learning is growing tremendously. Thus, Deep Learning Cookbook in R aims to provide a crash course in building different deep learning models. The application of deep learning is demonstrated through structured, unstructured, image, and audio case studies. The book will also cover transfer learning and how to utilize the power of GPU to enhance the computation efficiency of the deep learning model.

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