| Description |
1 online resource (301 pages) |
| Summary |
This book will help you understand how GANs architecture works using PyTorch. You will get familiar with the most flexible deep learning toolkit and use it to transform ideas into actual working codes. You will apply GAN models to areas like computer vision, multimedia and natural language processing using a sample-generation perspective. |
| Contents |
Section 1. Introduction to GANs and PyTorch.Generative Adversarial Networks Fundamentals ; Getting Started with PyTorch 1.3 ; Best Practices for Model Design and Training -- Section 2. Typical GAN Models for Image Synthesis. Building Your First GAN with PyTorch ; Generating Images Based on Label Information ; Image-to-Image Translation and Its Applications ; Image Restoration with GANs ; Training Your GANs to Break Different Models ; Image Generation from Description Text ; Sequence Synthesis with GANs ; Reconstructing 3D models with GANs. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Python.
|
|
Mathematical theory of computation. |
|
Machine learning. |
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Human-computer interaction. |
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Neural networks & fuzzy systems. |
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Computers -- Machine Theory. |
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Computers -- Social Aspects -- Human-Computer Interaction. |
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Computers -- Neural Networks. |
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Machine learning |
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Natural language processing (Computer science) |
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Neural networks (Computer science) |
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Python (Computer program language) |
| Added Author |
Walters, Greg.
|
| Other Form: |
Print version: Hany, John. Hands-On Generative Adversarial Networks with Pytorch 1. x : Implement Next-Generation Neural Networks to Build Powerful GAN Models Using Python. Birmingham : Packt Publishing, Limited, ©2019 9781789530513 |
| ISBN |
9781789534283 |
|
1789534283 |
|
9781789530513 |
|
