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008			230304s2022 si | s |||| 0|eng d
020			_a9789811651601
024	7		_a10.1007/978-981-16-5160-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA345 _b2022 EB
100	1		_aMahalle, Parikshit N. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9671611
245	1	0	_aFoundations of Data Science for Engineering Problem Solving _cby Parikshit Narendra Mahalle, Gitanjali Rahul Shinde, Priya Dudhale Pise, Jyoti Yogesh Deshmukh
250			_a1st edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIV, 117 páginas) _b58 ilustraciones, 50 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aStudies in Big Data _x2197-6511 _v94
505	0		_aIntroduction to Data Science -- Data Collection and Preparation -- Data Analysis and Machine learning Algorithms -- Data Visualization Tools and Data Modelling -- Data Science in Information, Communication and Technology -- Data Science in Civil & Mechanical Engineering -- Data Science in Clinical Decision System -- Conclusions.
520			_aThis book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
988			_aSpringer_Robotics_2022
650		7	_2embne _9669177 _aIngeniería _xProceso de datos
650		7	_2embne _9495511 _aDatos masivos
650		7	_2embne _9145622 _aSistemas de visualización de información
700	1		_9686019 _aShinde, Gitanjali Rahul, _d1983- _eautor
700	1		_9687159 _aPise, Priya Dudhale _eautor
700	1		_9687160 _aDeshmukh, Jyoti Yogesh _eautor
776	0	8	_iPrinted edition: _z9789811651595
776	0	8	_iPrinted edition: _z9789811651618
776	0	8	_iPrinted edition: _z9789811651625
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-5160-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _eIG _zSI