| Description |
1 online resource (228 pages) |
| Bibliography |
Includes bibliographical references. |
| Summary |
The Go ecosystem comprises some really powerful Deep Learning tools. This book shows you how to use these tools to train and deploy scalable Deep Learning models. You will explore a number of modern Neural Network architectures such as CNNs, RNNs, and more. By the end, you will be able to train your own Deep Learning models from scratch, using ... |
| Contents |
Table of ContentsIntroduction to Deep Learning in GoWhat Is a Neural Network and How Do I Train One?Beyond Basic Neural Networks -- Autoencoders and RBMsCUDA -- GPU-Accelerated TrainingNext Word Prediction with Recurrent Neural NetworksObject Recognition with Convolutional Neural NetworksMaze Solving with Deep Q-NetworksGenerative Models with Variational AutoencodersBuilding a Deep Learning PipelineScaling Deployment. |
| Subject |
Machine learning.
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Go (Computer program language)
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Apprentissage automatique. |
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Go (Langage de programmation) |
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Go (Computer program language) |
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Machine learning |
| Added Author |
Chua, Darrell, author.
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| Other Form: |
Print version: Seneque, Gareth. Hands-On Deep Learning with Go : A Practical Guide to Building and Implementing Neural Network Models Using Go. Birmingham : Packt Publishing, Limited, ©2019 9781789340990 |
| ISBN |
9781789347883 (electronic bk.) |
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1789347882 (electronic bk.) |
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(pbk.) |
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