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A Primer on Generative Adversarial Networks / by Sanaa Kaddoura
(SpringerBriefs in Computer Science. ISSN:21915776)

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2023
大きさ	X, 84 p. 1 illus : online resource
著者標目	*Kaddoura, Sanaa author SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0002957	Computer Scinece R0 2005-6,2022-3				9783031326615

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一般注記	Overview of GAN Structure -- Your First GAN -- Real World Applications -- Conclusion 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 HTTP:URL=https://doi.org/10.1007/978-3-031-32661-5
件　名	LCSH:Machine learning LCSH:Signal processing LCSH:Computer simulation FREE:Machine Learning FREE:Signal, Speech and Image Processing FREE:Computer Modelling
分　類	LCC:Q325.5-.7 DC23:006.31
書誌ID	EB00002345
ISBN	9783031326615