GANs in action : deep learning with generative adversarial networks / Jakub Langr, Vladimir Bok.
Material type:
TextPublication details: New York: Manning Publications Co. 2019Edition: 1st edDescription: xxiii, 214 pages : illustrations ; 24 cmISBN: - 9781617295560
- Generative Adversarial Networks in action
- 006.31 23 L285g
| Item type | Current library | Call number | Vol info | Copy number | Status | Barcode | |
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Library, Independent University, Bangladesh (IUB) Reference Stacks | 006.31 L285g (Browse shelf(Opens below)) | 2019 | 01 | Not For Loan | 029870 | |
Books
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Library, Independent University, Bangladesh (IUB) General Stacks | 006.31 L285g (Browse shelf(Opens below)) | 2019 | 02 | Available | 029871 |
Includes bibliographical references and index.
Introduction to GANs and generative modeling -- Advanced topics in GANs -- Where to go from here.
Generative Adversarial Networks, GANs, are an incredible AI technology capable of creating images, sound, and videos that are indistinguishable from the "real thing". By pitting two neural networks against each other, one to generate fakes and one to spot them, GANs rapidly learn to produce photo-realistic faces and other media objects. With the potential to produce stunningly realistic animations or shocking deepfakes, GANs are a huge step forward in deep learning systems. "GANs in action" teaches you to build and train your own Generative Adversarial Networks. You'll start by creating simple generator and discriminator networks that are the foundation of GAN architecture. Then, following numerous hands-on examples, you'll train GANs to generate high-resolution images, image-to-image translation, and targeted data generation. Along the way, you'll find pro tips for making your system smart, effective, and fast.
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