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Hands-On Deep Learning with Go

You're reading from   Hands-On Deep Learning with Go A practical guide to building and implementing neural network models using Go

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789340990
Length 242 pages
Edition 1st Edition
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Authors (2):
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Darrell Chua Darrell Chua
Author Profile Icon Darrell Chua
Darrell Chua
Gareth Seneque Gareth Seneque
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Gareth Seneque
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Deep Learning in Go, Neural Networks, and How to Train Them
2. Introduction to Deep Learning in Go FREE CHAPTER 3. What Is a Neural Network and How Do I Train One? 4. Beyond Basic Neural Networks - Autoencoders and RBMs 5. CUDA - GPU-Accelerated Training 6. Section 2: Implementing Deep Neural Network Architectures
7. Next Word Prediction with Recurrent Neural Networks 8. Object Recognition with Convolutional Neural Networks 9. Maze Solving with Deep Q-Networks 10. Generative Models with Variational Autoencoders 11. Section 3: Pipeline, Deployment, and Beyond!
12. Building a Deep Learning Pipeline 13. Scaling Deployment 14. Other Books You May Enjoy

Introducing DL

We will now offer a high-level view of why DL is important and how it fits into the discussion about AI. Then, we will look at the historical development of DL, as well as current and future applications.

Why DL?

So, who are you, dear reader? Why are you interested in DL? Do you have your private vision for AI? Or do you have something more modest? What is your origin story?

In our survey of colleagues, teachers, and meetup acquaintances, the origin story of someone with a more formal interest in machines has a few common features. It doesn't matter much if you grew up playing games against the computer, an invisible enemy who sometimes glitched out, or if you chased down actual bots in id Software&apos...

You have been reading a chapter from
Hands-On Deep Learning with Go
Published in: Aug 2019
Publisher: Packt
ISBN-13: 9781789340990
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