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020			_a9781098125974 _q(paperback)
020			_a1098125975 _q(paperback)
035			_a(OCoLC)on1346503549
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042			_alccopycat
050	0	0	_aQA76.73.P98 _bG45 2023
082	0	4	_223 _a006.3/1 G377h 2023
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.
260			_aBeijing : _bO'Reilly, _c2023.
300			_axxv, 834 pages : _billustrations (chiefly color) ; _c24 cm.
500			_aPrevious editions: 2019, 2017.
504			_aIncludes bibliographical references and index.
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"--
526			_aComputer Science & Engineering
630	0	0	_aTensorFlow.
650		0	_aPython (Computer program language)
650		0	_aMachine learning. _93635
650		0	_aArtificial intelligence. _95339
650		6	_aApprentissage automatique.
650		6	_aPython (Langage de programmation)
650		6	_aIntelligence artificielle.
650		7	_aartificial intelligence. _2aat _95339
650		7	_aArtificial intelligence _2fast _95339
650		7	_aMachine learning _2fast _93635
650		7	_aPython (Computer program language) _2fast
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999			_c7878 _d7878