LEADER 04478nam 22006855 450 001 9910845486103321 005 20241219142426.0 010 $a9789819704484 010 $a9819704480 024 7 $a10.1007/978-981-97-0448-4 035 $a(MiAaPQ)EBC31221972 035 $a(Au-PeEL)EBL31221972 035 $a(DE-He213)978-981-97-0448-4 035 $a(CKB)30995669800041 035 $a(EXLCZ)9930995669800041 100 $a20240319d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Analytics and Machine Learning $eNavigating the Big Data Landscape /$fedited by Pushpa Singh, Asha Rani Mishra, Payal Garg 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (357 pages) 225 1 $aStudies in Big Data,$x2197-6511 ;$v145 311 08$a9789819704477 311 08$a9819704472 327 $aChapter 1. Introduction to Data Analytics, Big Data, and Machine Learning -- Chapter 2. Fundamentals of Data Analytics and Lifecycle -- Chapter 3. Building Predictive Models with Machine Learning -- Chapter 4. Stream data model and architecture -- Chapter 5. Leveraging Big Data for Data Analytics -- Chapter 6. Advanced Techniques in Data Analytics -- Chapter 7. Scalable Machine Learning with Big Data -- Chapter 8. Big Data Analytics Framework using Machine Learning on Massive Datasets -- Chapter 9. Deep-learning Techniques in Big-Data analytics -- Chapter 10. Data Privacy and Ethics in Data Analytics -- Chapter 11. Practical Implementation of Machine Learning Techniques & data analytics using R -- Chapter 12. Real-World Applications of Data Analytics, Big Data, and Machine Learning -- Chapter 13. Implementing Data-Driven Innovation in Organizations -- Chapter 14. Business Transformation using Big Data Analytics and Machine Learning -- Chapter 15. Future Trends and Emerging Opportunities in HealthAnalytics -- Chapter 16. Future Trends in Data Analytics and Machine Learning. 330 $aThis book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, big data, and machine learning solutions in their own organizations. The book discusses the transformative power of data analytics and big data in various industries and sectors and how machine learning applications have revolutionized exploration by enabling advanced data analysis techniques for mapping, geospatial analysis, and environmental monitoring, enhancing our understanding of the world and its dynamic processes. This book explores how big data explosion, the power of analytics and machine learning revolution can bring new prospects and opportunities in the dynamic and data-rich landscape. It highlights the future research directions in data analytics, big data, and machine learning that explores the emerging trends, challenges, and opportunities in these fields by covering interdisciplinary approaches such as handling and analyzing real-time and streaming data. 410 0$aStudies in Big Data,$x2197-6511 ;$v145 606 $aQuantitative research 606 $aMachine learning 606 $aNatural language processing (Computer science) 606 $aData Analysis and Big Data 606 $aMachine Learning 606 $aNatural Language Processing (NLP) 606 $aDades massives$2thub 606 $aAprenentatge automātic$2thub 608 $aLlibres electrōnics$2thub 615 0$aQuantitative research. 615 0$aMachine learning. 615 0$aNatural language processing (Computer science). 615 14$aData Analysis and Big Data. 615 24$aMachine Learning. 615 24$aNatural Language Processing (NLP). 615 7$aDades massives 615 7$aAprenentatge automātic 676 $a001.422 676 $a005.7 700 $aSingh$b Pushpa$01734219 701 $aMishra$b Asha Rani$01734220 701 $aGarg$b Payal$01734221 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910845486103321 996 $aData Analytics and Machine Learning$94150852 997 $aUNINA