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003			ES-MaUEC
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008			210811s2022 sz | s |||| 0|eng d
020			_a9783030758554
024	7		_a10.1007/978-3-030-75855-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2022 EB
245	0	0	_aDeep Learning in Data Analytics : _bRecent Techniques, Practices and Applications _cedited by Debi Prasanna Acharjya, Anirban Mitra, Noor Zaman
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XX, 266 páginas) _b114 ilustraciones, 92 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 _v91
505	0		_aStudy on Discrete Action Sequences using Deep Emotional Intelligence -- A Novel Noise Removal Technique Influenced by Deep Convolutional Autoencoders on Mammograms -- A High Security Framework through Human Brain using Algo Mixture Model Deep Learning Algorithm -- Knowledge Framework for Deep Learning: Congenital Heart Disease -- Computing System and Machine Learning -- Automatic Image Segmentation by Ranking based SVM in Convolutional Neural Network on Diabetic Fundus Image.
520			_aThis book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.
988			_aSpringer_Robotics_2022
650		7	_2embne _9166090 _aAprendizaje automático
776	0	8	_iPrinted edition: _z9783030758547
776	0	8	_iPrinted edition: _z9783030758561
776	0	8	_iPrinted edition: _z9783030758578
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-75855-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _eu _zSI