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008			190924s2020 gw a o |||| 0|eng d
020			_a9783030266226
024	7		_a10.1007/978-3-030-26622-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2020 EB
100	1		_aJoshi, Ameet V. _eautor _9671602
245	1	0	_aMachine learning and artificial intelligence _cby Ameet V. Joshi
250			_aFirst edition
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XXII, 261 páginas) _b98 ilustraciones, 94 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 -- Part I Introduction to AI and ML -- Essential concepts in AL and ML -- Part II Techniques for Static Machine Learning Models -- Perceptron and Neural Networks -- Decision Trees -- Advanced Decision Trees -- Support Vector Machines -- Probabilistic Models -- Deep Learning -- Part III Techniques for Dynamic Machine Learning Models -- Autoregressive and Moving Average Models -- Hidden Markov Models and Conditional Random Fields -- Recurrent Neural Networks -- Part IV Applications -- Classification Regression -- Ranking -- Clustering -- Recommendations -- Next Best Actions -- Designing ML Pipelines -- Using ML Libraries -- Azure Machine Learning Studio -- Conclusions.
520	3		_aThis book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible. Presents a full reference to artificial intelligence and machine learning techniques - in theory and application; Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible; Connects all ML and AI techniques to applications and introduces implementations.
650		7	_2embne _aAprendizaje automático _9166090
650		7	_2embne _aInteligencia artificial _9413115
776	0	8	_iPrinted edition: _z9783030266219
776	0	8	_iPrinted edition: _z9783030266233
776	0	8	_iPrinted edition: _z9783030266240
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-26622-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Engineering_2020
998			_aSI _cm _dz _feng _ggw _h0 _b12/2019 _eel _zSI