GANs in Action: Deep Learning with Generative Adversarial Networks
Overview & Synopsis
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.
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freecomputerbooks.com)
Document Information
| Document Title | GANs in Action: Deep Learning with Generative Adversarial Networks |
|---|---|
| Author / Organization | Jakub Langr and Vladimir Bok |
| Subject & Discipline | Neural Networks and Deep Learning, Python Programming, Machine Learning, Artificial Intelligence, Data Science |
| Categories | Neural Networks and Deep Learning |
| Publication Year | 2019 |
| ISBN | 1617295566 |
| Resource Verification | External Reading Page / Repository |
| Alternative Mirrors & Links | |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
|
| File Format | application/pdf (Portable Document Format) |
| Language | ENGLISH |
| Catalog ID | DOC-93351 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |
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