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020			_a9781098125974 _q(paperback)
020			_a1098125975 _q(paperback)
035			_a(OCoLC)on1346503549
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050	0	0	_aQA76.73.P98 _bG45 2023
082	0	4	_a006.31 _223
090			_a006.31 _bG377h
100	1		_aGéron, Aurélien, _eauthor.
245	1	0	_aHands-on machine learning with Scikit-Learn, Keras and TensorFlow : _bconcepts, tools, and techniques to build intelligent systems / _cAurélien Géron.
250			_aThird edition.
264		1	_aBeijing : _bO'Reilly Media, Inc., _c2023.
264		4	_c©2023
300			_axxv, 834 pages : _billustrations (chiefly color) ; _c24 cm
336			_atext _btxt _2rdacontent
336			_astill image _bsti _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
500			_aPrevious editions: 2019, 2017.
505	0		_aThe fundamentals of machine learning. The machine learning landscape ; End-to-end machine learning project ; Classification ; Training models ; Support vector machines ; Decision trees ; Ensemble learning and random forests ; Dimensionality reduction ; Unsupervised learning techniques -- Neural networks and deep learning. Introduction to artificial neural networks with Keras ; Training deep neural networks ; Custom models and training with TensorFlow ; Loading and preprocessing data with TensorFlow ; Deep computer vision using convolutional neural networks ; Processing sequences using RNNs and CNNs ; Natural language processing with RNNs and attention ; Autoencoders, GANs, and diffusion models ; Reinforcement learning ; Training and deploying TensorFlow models at scale.
520			_a"Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started"-- _cPage 4 of cover.
630	0	0	_aTensorFlow.
650		0	_aPython (Computer program language)
650		0	_aMachine learning.
650		0	_aArtificial intelligence.
650		6	_aApprentissage automatique.
650		6	_aPython (Langage de programmation)
650		6	_aIntelligence artificielle.
650		7	_aartificial intelligence.
650		7	_aArtificial intelligence
650		7	_aMachine learning
650		7	_aPython (Computer program language)
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2ddc _cL _k006.31 _mG377h
999			_c2704 _d2704