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008			200504s2020 si a o |||| 0|eng d
020			_a9789811533570
024	7		_a10.1007/978-981-15-3357-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2020 EB
245	0	0	_aApplications of Machine Learning / _cedited by Prashant Johri, Jitendra Kumar Verma, Sudip Paul
250			_aFirst edition
264		1	_aSingapore _bSpringer Singapore : _bImprint: Springer _c2020
300			_a1 recurso en línea (XXII, 394 páginas) _b158 ilustraciones, 112 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aAlgorithms for Intelligent Systems _x2524-7565
490	0		_aEngineering (Springer-11647)
505	0		_aStatistical Learning Process for the Reduction of Sample Collection Assuring a Desired Level of Confidence -- Sentiment Analysis on Google Play Store Data using Deep Learning -- Managing the Data Meaning in the Data Stream Processing: A Systematic Literature Mapping -- Tracking an Object using Traditional MS (Mean Shift) and CBWH MS (Mean Shift) Algorithm with Kalman Filter -- Transfer Learning and Domain Adaptation for Named Entity Recognition -- Knowledge Graph from Informal Text: Architecture, Components, Algorithms and Applications -- Neighborhood-based Collaborative Recommendations: An Introduction -- Classification of Arabic Texts Using Singular Value Decomposition and Fuzzy C-Means Algorithms -- Echo State Network Based Nonlinear Channel Equalization in Wireless Communication System -- Melody Extraction from Music: A Comprehensive Study -- Comparative Analysis of Combined Gas Turbine-Steam Turbine Power Cycle Performance by Using Entropy Generation and Statistical Methodology -- Data Mining - A Tool for Handling Huge Voluminous Data -- Improved Training Pattern in Back Propagation Neural Networks Using Holt-Winters' Seasonal Method and Gradient Boosting Model -- Ensemble of Multi-headed Machine Learning Architectures for Time-series Forecasting of Healthcare Expenditures -- Applying Soft Computing Approaches To Investigate Software Fault Proneness in Agile Software Development Environment.
520	3		_aThis book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
988			_aSpringer_Engineering_23062020
650		7	_aAprendizaje automático _2embne _9166090
700	1		_aJohri, Prashant _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aVerma, Jitendra Kumar _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aPaul, Sudip _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service) _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729
776	0	8	_iPrinted edition: _z9789811533563
776	0	8	_iPrinted edition: _z9789811533587
776	0	8	_iPrinted edition: _z9789811533594
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-3357-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2020 _dz _eo _zSI