000			02096nam\a2200301\a\4500
001			57891
005			20260707121813.0
008			260707t20192019nyua b 001 0 eng d
020			_a9781617295560
040			_aYDX _beng _cYDX _erda _dOCLCQ _dTFW _dOCLCO _dBDX _dJRZ _dBD-DhIUB
082	0	4	_a006.31 _223 _bL285g
100	1		_aLangr, Jakub _eauthor.
245	1	0	_aGANs in action : _bdeep learning with generative adversarial networks / _cJakub Langr, Vladimir Bok.
246	3		_aGenerative Adversarial Networks in action
250			_a1st ed.
260			_aNew York: _bManning Publications Co. _c2019
300			_axxiii, 214 pages : _billustrations ; _c24 cm
504			_aIncludes bibliographical references and index.
505	0		_aIntroduction to GANs and generative modeling -- Advanced topics in GANs -- Where to go from here.
520			_aGenerative 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.
526			_aCSE _bps _lREF
541			_aOmni concept
650		0	_aMachine learning _xTechnological innovations.
650		0	_aArtificial intelligence _xComputer programs.
700	1		_aBok, Vladimir _eauthor.
942			_2ddc _cBK
999			_c57891 _d58065