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Deep Learning Essentials

You're reading from   Deep Learning Essentials Your hands-on guide to the fundamentals of deep learning and neural network modeling

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781785880360
Length 284 pages
Edition 1st Edition
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Authors (3):
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Wei Di Wei Di
Author Profile Icon Wei Di
Wei Di
Anurag Bhardwaj Anurag Bhardwaj
Author Profile Icon Anurag Bhardwaj
Anurag Bhardwaj
Jianing Wei Jianing Wei
Author Profile Icon Jianing Wei
Jianing Wei
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Table of Contents (12) Chapters Close

Preface 1. Why Deep Learning? 2. Getting Yourself Ready for Deep Learning FREE CHAPTER 3. Getting Started with Neural Networks 4. Deep Learning in Computer Vision 5. NLP - Vector Representation 6. Advanced Natural Language Processing 7. Multimodality 8. Deep Reinforcement Learning 9. Deep Learning Hacks 10. Deep Learning Trends 11. Other Books You May Enjoy

Deep learning models

In this section, we will dive into three popular deep learning models one by one: CNNs, Restricted Boltzmann Machines (RBM), and the recurrent neural network (RNN).

Convolutional Neural Networks

Convolutional Neural Networks are biologically-inspired variants of the multilayer perceptron and have been proven to be very effective in areas such as image recognition and classification. ConvNets have been successfully applied when identifying faces, objects, and traffic signs as well as powering vision in robots and self-driving cars. CNNs exploit spatially-local correlation by enforcing a local connectivity pattern between neurons of adjacent layers. In other words, the inputs of hidden units in the layer...

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