EAN: 9783031326608

SPRINGERBRIEFS IN COMPUTER SCIENCE A PRIMER O...

This book is meant for readers who want to understand GANs without the need for a strong
mathematical background. Moreover  it covers the practical applications of GANs  making it an
excellent resource for beginners. A Primer on Generative Adversarial Networks is suitable for
researchers  developers  students  and anyone who wishes to learn about GANs. It is assumed
that the reader has a basic understanding of machine learning and neural networks. The book
comes with ready-to-run scripts that readers can use for further research. Python is used as
the primary programming language  so readers should be familiar with its basics. The book
starts by providing an overview of GAN architecture  explaining the concept of generative
models. It then introduces the most straightforward GAN architecture  which explains how GANs
work and covers the concepts of generator and discriminator. The book then goes into the more
advanced real-world applications of GANs  such as human face generation  deep fake  CycleGANs 
and more.By the end of the book  readers will have an essential understanding of GANs and be
able to write their own GAN code. They can apply this knowledge to their projects  regardless
of whether they are beginners or experienced machine learning practitioners.

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