LEADER 04011oam 2200589K 450 001 9910860823703321 005 20230127182431.0 010 $a1-000-09828-1 010 $a0-429-32299-2 010 $a1-000-09830-3 024 7 $a10.1201/9780429322990 035 $a(CKB)4100000011340142 035 $a(MiAaPQ)EBC6260314 035 $a(OCoLC)1178954689$z(OCoLC)1165388047 035 $a(OCoLC-P)1178954689 035 $a(FlBoTFG)9780429322990 035 $a(PPN)266621694 035 $a(EXLCZ)994100000011340142 100 $a20200618h20212021 my 0 101 0 $aeng 135 $aurcnu---unuuu 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 00$aBig data, IoT, and machine learning $etools and applications /$feditors, Rashmi Agrawal, Marcin Paprzycki, Neha Gupta 205 $a1st Edition. 210 1$aBoca Raton, FL :$cCRC Press,$d2021. 210 4$dİ2021 215 $a1 online resource (xvii, 319 pages) $cillustrations (some colour) 225 0 $aInternet of Everything (IoE): security and privacy paradigm 311 $a0-367-53121-6 311 $a0-367-33674-X 320 $aIncludes bibliographical references and index. 327 $aSection I: Applications of Machine Learning 1. Machine Learning Classifiers 2. Dimension Reduction Techniques 3. Reviews Analysis of Apple Store Applications Using Supervised Machine Learning 4. Machine Learning for Biomedical and Health Informatics 5. Meta-Heuristic Algorithms: A Concentration on the Applications in Text Mining 6. Optimizing Text Data in Deep Learning: An Experimental Approach Section II: Big Data, Cloud and Internet of Things 7. Latest Data and Analytics Technology Trends That Will Change Business Perspectives 8. A Proposal Based on Discrete Events for Improvement of the Transmission Channels in Cloud Environments and Big Data 9. Heterogeneous Data Fusion for Healthcare Monitoring: A Survey 10. Discriminative and Generative Model Learning for Video Object Tracking 11. Feature, Technology, Application, and Challenges of Internet of Things 12. Analytical Approach to Sustainable Smart City Using IoT and Machine Learning 13. Traffic Flow Prediction with Convolutional Neural Network Accelerated by Spark Distributed Cluster 330 $aThe idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases 606 $aBig data 606 $aInternet of things 606 $aMachine learning 615 0$aBig data. 615 0$aInternet of things. 615 0$aMachine learning. 676 $a005.7 676 $a005.7 702 $aAgrawal$b Rashmi 702 $aPaprzycki$b Marcin 702 $aGupta$b Neha 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9910860823703321 996 $aBig data, IoT, and machine learning$94166817 997 $aUNINA