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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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Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Machine Learning with R - Second Edition
Brett Lantz

ISBN: 978-1-78439-390-8

Harness the power of R to build common machine learning algorithms with real-world data science applications
Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results
Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems
Classify your data with Bayesian and nearest neighbor methods
Predict values by using R to build decision trees, rules, and support vector machines
Forecast numeric values with linear regression, and model your data with neural networks
Evaluate and improve the performance of machine learning models
Learn specialized machine learning techniques for text...

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