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710	2		_aSpringerLink (Online service) _9106996
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008			190507s2019 gw a o |||| 0|eng d
020			_a9783030157296
024	7		_a10.1007/978-3-030-15729-6 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aQ325.5 _b2019 EB
100			_aRebala, Gopinath _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673316
245	1	3	_aAn Introduction to Machine Learning _cby Gopinath Rebala, Ajay Ravi, Sanjay Churiwala.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019.
300			_a1 recurso en línea (XXII, 263 páginas) _b83 ilustraciones, 77 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
505	0		_aIntroduction -- Basics before Machine Learning -- Learning Models -- Regression -- Improving Further -- Classification -- Clustering (unsupervised Learning) -- Random Forests -- Testing the Algorithm and the Network -- Neural Network -- Reinforcement Learning -- Deep Learning -- Principal Component Analysis -- Anomaly Detection -- Recommender System -- Feature Search/Convolution -- Natural Language Processing -- Language Translation -- AlphaGo -- Data Quality -- System Improvement -- Software stack -- Hardware Implementations. .
520	3		_aJust like electricity, Machine Learning will revolutionize our life in many ways - some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning techniques and algorithms. Many of the mathematical concepts are explained in an intuitive manner. The book starts with an overview of machine learning and the underlying Mathematical and Statistical concepts before moving onto machine learning topics. It gradually builds up the depth, covering many of the present day machine learning algorithms, ending in Deep Learning and Reinforcement Learning algorithms. The book also covers some of the popular Machine Learning applications. The material in this book is agnostic to any specific programming language or hardware so that readers can try these concepts on whichever platforms they are already familiar with. Offers a comprehensive introduction to Machine Learning, while not assuming any prior knowledge of the topic; Provides a complete overview of available techniques and algorithms in conceptual terms, covering various application domains of machine learning; Not tied to any specific software language or hardware implementation. .
988			_aPrimersemestre_2019_Engineering
650		7	_2embne _aAprendizaje automático _9166090
700	1		_aChuriwala, Sanjay. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aRavi, Ajay. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783030157289
776	0	8	_iPrinted edition: _z9783030157302
776	0	8	_iPrinted edition: _z9783030157319
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-15729-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_dz _feng _ggw _h0 _b04/2020 _ea _zSI