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R Deep Learning Essentials

You're reading from   R Deep Learning Essentials A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781788992893
Length 378 pages
Edition 2nd Edition
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Authors (2):
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Joshua F. Wiley Joshua F. Wiley
Author Profile Icon Joshua F. Wiley
Joshua F. Wiley
Mark Hodnett Mark Hodnett
Author Profile Icon Mark Hodnett
Mark Hodnett
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with Deep Learning FREE CHAPTER 2. Training a Prediction Model 3. Deep Learning Fundamentals 4. Training Deep Prediction Models 5. Image Classification Using Convolutional Neural Networks 6. Tuning and Optimizing Models 7. Natural Language Processing Using Deep Learning 8. Deep Learning Models Using TensorFlow in R 9. Anomaly Detection and Recommendation Systems 10. Running Deep Learning Models in the Cloud 11. The Next Level in Deep Learning 12. Other Books You May Enjoy

Other Books You May Enjoy

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R Deep Learning Projects
Yuxi (Hayden) Liu, Pablo Maldonado

ISBN: 9781788478403

  • Instrument Deep Learning models with packages such as deepnet, MXNetR, Tensorflow, H2O, Keras, and text2vec
  • Apply neural networks to perform handwritten digit recognition using MXNet
  • Get the knack of CNN models, Neural Network API, Keras, and TensorFlow for traffic sign classification
  • Implement credit card fraud detection with Autoencoders
  • Master reconstructing images using variational autoencoders
  • Wade through sentiment analysis from movie reviews
  • Run from past to future and vice versa with bidirectional Long Short-Term Memory (LSTM) networks
  • Understand the applications of Autoencoder Neural Networks in clustering and dimensionality reduction

R Deep Learning Cookbook
Dr. PKS Prakash, Achyutuni...

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