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005			20240729155143.0
008			230208b vm ||||| |||| 00| | vie d
020			_a9780262035613
040			_aISVNU
041			_aeng
082			_bDEE _a006.31
100			_aGoodfellow, Ian
245			_aDeep Learning / _cIan Goodfellow, Yoshua Bengio, Aaron Courville
250			_aIllustrated edition
260			_aCambridge, MA : MIT Press _bThe MIT Press, _c 2013
300			_a800 p. ; _c28 cm.
520			_aDeep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
650			_aMachine learning _aArtificial Intelligent
650			_aDeep learning (Machine learning)
653			_aHọc bằng máy
653			_aTrí tuệ nhân tạo
700			_aBengio, Yoshua
700			_aCourville, Aaron
911			_aH.Quyên
918			_aINS3080
919			_aChương trình AIT _bSách tham khảo chương trình AIT _cINS3080 _dTrí tuệ nhân tạo _dArtificial Intelligent
942			_2ddc _cBK
999			_c10302 _d10302