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R Deep Learning Projects

You're reading from R Deep Learning Projects Master the techniques to design and develop neural network models in R

Product type Paperback

Published in Feb 2018

Publisher Packt

ISBN-13 9781788478403

Length 258 pages

Edition 1st Edition

Languages

R

Tools

Keras

Concepts

Deep Learning

Authors (2):

Yuxi (Hayden) Liu

Pablo Maldonado

View More author details

Table of Contents (7) Chapters

Preface

1. Handwritten Digit Recognition Using Convolutional Neural Networks

2. Traffic Sign Recognition for Intelligent Vehicles FREE CHAPTER

3. Fraud Detection with Autoencoders

4. Text Generation Using Recurrent Neural Networks

5. Sentiment Analysis with Word Embeddings

6. Other Books You May Enjoy

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Who this book is for

This book is meant mainly for two types of readers: professionals who use R in their daily work and want to know some of the tricks and best practices that we have discovered in our projects, and anyone who wants to jump into the field of deep learning with concrete use cases in mind. This is not a tutorial in R or machine learning; it is rather a real-world showcase of how deep learning can be used in industry, with examples borrowed from our own experience.

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