000			02584cam a22003497a 4500
001			1347020175
003			APU
005			20240605144832.0
007			cr |n|||||||||
008			240605s2022 cau o 001 0 eng d
020			_a9781098122478 (paperback)
020			_a109812247X
020			_z1098125975
020			_z9781098125974
035			_a(OCoLC)1347020175
037			_a9781098125967 _bO'Reilly Media
040			_aYDX _benglish _cYDX _dSY
050		4	_aQ325.5 _b.G476 2023 c.1
082	0	4	_a006.3/1 _223/eng/20221011
100	1		_aGeron, Aurelien, _eauthor. _946197
245	1	0	_aHands-on machine learning with Scikit-Learn, Keras, and Tensorflow : _bconcepts, tools, and techniques to build intelligent systems / _cAurelien Geron.
250			_aThird edition
260			_aSebastopol, California : _bO'Reilly Media, Inc., _c©2022.
300			_axxv, 834 pages : _billustrations (chiefly color) ; _c24 cm.
500			_aIncludes index
520			_aThrough 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 bestselling 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 Aur©♭lien G©♭ron 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. Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning
630	0	0	_aTensorFlow _946198
650		0	_aMachine learning
650		0	_aArtificial intelligence
650		0	_aPython (Computer program language)
942			_2lcc _cBook
999			_c384116 _d384116