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100   $a20210929d2022      u|         0
101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 10$aMachine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) /$fedited by Rajiv Misra, Rudrapatna K. Shyamasundar, Amrita Chaturvedi, Rana Omer
205   $a1st ed. 2022.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022.
215   $a1 online resource (372 pages)
225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v256
300   $aIncludes index.
311   $a3-030-82468-3 
327   $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.
330   $aThis edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets?i.e., big data?to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.
410  0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v256
606   $aEngineering?Data processing
606   $aComputational intelligence
606   $aMachine learning
606   $aBig data
606   $aData Engineering
606   $aComputational Intelligence
606   $aMachine Learning
606   $aBig Data
615  0$aEngineering?Data processing.
615  0$aComputational intelligence.
615  0$aMachine learning.
615  0$aBig data.
615 14$aData Engineering.
615 24$aComputational Intelligence.
615 24$aMachine Learning.
615 24$aBig Data.
676   $a006.31
702   $aMisra$b Rajiv
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910522952603321
996   $aMachine learning and big data analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)$92886943
997   $aUNINA