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003			OSt
005			20251117095846.0
008			251106b |||||||| |||| 00| 0 eng d
020			_a9789352139248 _q(paperback)
020			_a9352139240
040			_erda _aSAIU
082			_223 _a005.6
100			_qKoul, Anirudh, _eauthor
245	1	0	_aPractical deep learning for cloud, mobile, and edge : _breal-world AI and computer-vision projects using Python, Keras, and TensorFlow / _cAnirudh Koul, Siddha Ganju, and Meher Kasam.
246	3	0	_aReal-world AI and computer-vision projects using Python, Keras, and TensorFlow
246	3		_aReal-world Artificial Intelligence and computer-vision projects using Python, Keras, and TensorFlow
250			_aFirst Edition. _bThird Indian Reprint
260			_aIndia : _bShroff / O'Reilly Media, _c2019.
264	1		_aIndia : _bShroff / O'Reilly Media, _c2019.
264	4		_c©2020
300			_axiv, 588 pages : _billustrations ; _c24 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
500			_aIncludes index
505			_aExploring the landscape of Artificial Intelligence -- What's in the picture: image classification with Keras -- Cats versus dogs: transfer learning in 30 lines with Keras -- Building a reverse image search engine: understanding embeddings -- From novice to master predictor: maximizing convolutional neural network accurcy -- Maximizing speed and performance of TensorFlow: a handy checklist -- Practical tools, tips, and tricks -- Cloud APIs for computer vision: up and running in 15 minutes -- Scalable inference serving on Cloud with TensorFlow Serving and KubeFlow -- AI in the browser with TensorFlow.js and mI5.js -- Real-time object classification on iOS with Core ML -- Not hotdog on iOS with Core ML and Create ML -- Shazam for food: developing android apps with TensorFlow Lite and ML Kit -- Building the purrfect cat locator app with TensorFlow Object Detection API -- Becoming a maker: exploring embedded AI at the edge -- Simulating a self-driving car using end-to-end deep learning with Keras -- Building an autonomous car in under an hour: reinforcement learning with AWS DeepRacer
520			_aWhether you're a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use.
630	0	0	_aTensorFlow
650		0	_aPython (Computer program language)
650		0	_aArtificial intelligence
650		0	_aApplication software
650		0	_aMachine learning
650		0	_aCloud computing
700	1		_aGanju, Siddha, _eauthor
700	1		_aKasam, Meher, _eauthor
942			_2ddc _cBK
999			_c6897 _d6897