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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? FREE CHAPTER 2. Getting Yourself Ready for Deep Learning 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

Popular CNN architectures

Designing a perfect CNN architecture involves a large amount of experimentation and compute power. Hence, it is often non-trivial to achieve optimal CNN architecture design. Fortunately, a number of CNN architectures exist today that act as a good starting point for many developers and researchers as they wet their feet in designing a CNN network from scratch. In this section, we will go over some popular CNN architectures known today.

AlexNet

One of the earliest works in popularizing the use of CNNs in large-scale image classification, AlexNet was proposed by Alex Krizhevsky and their co-authors in 2012. It was submitted as an entry to the ImageNet challenge in 2012 and significantly outperformed...

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