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008			210929s2022 sz | s |||| 0|eng d
020			_a9783030824693
024	7		_a10.1007/978-3-030-82469-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2022 EB
245	0	0	_aMachine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) _cedited by Rajiv Misra, Rudrapatna K. Shyamasundar, Amrita Chaturvedi, Rana Omer
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XI, 362 páginas) _b226 ilustraciones, 147 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aLecture Notes in Networks and Systems _x2367-3389 _v256
505	0		_aEngagement Analysis of Students in Online Learning Environments -- Application of Artificial Intelligence to predict the Degradation of Potential mRNA Vaccines Developed To Treat SARS-CoV-2 -- An Application of Transfer Learning: Fine-Tuning BERT for Spam Email Classification -- MMAP : A Multi-Modal Automated Online Proctor -- Applying Extreme Gradient Boosting for Surface EMG based Sign Language recognition -- Review of Security Aspects of 51 Percent Attack on Blockchain -- Integrated Micro-video Recommender based on Hadoop and Web-Scrapper -- Automated Sleep Staging System based on Ensemble Learning Model using Single-Channel EEG signal -- Segregation and User Interactive Visualization of Covid- 19 Tweets using Text Mining Techniques -- Software Fault Prediction using Data Mining Techniques on Software Metrics.
520			_aThis edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets-i.e., big data-to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.
988			_aSpringer_Robotics_2022
650		7	_2embne _9166090 _aAprendizaje automático _vCongresos y asambleas
776	0	8	_iPrinted edition: _z9783030824686
776	0	8	_iPrinted edition: _z9783030824709
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-82469-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _eu _zSI