01190nam0 2200313 i 450 SUN001944320110223122648.10288-339-0789-920040712d1993 |0itac50 baitaIT|||| |||||ˆL'‰età di mezzoscritti di Elliott Jaques, Otto F. Kernberg, Clara M. ThompsonTorinoBollati Boringhieri1993154 p.18 cm.AdultiPsicanalisiFISUNC009557TorinoSUNL000001155.6621Kernberg, Otto F.SUNV013689Jaques, ElliottSUNV015606Thompson, Clara M.SUNV015608Bollati BoringhieriSUNV000104650Jaques, ElliotJaques, ElliottSUNV015607ITSOL20181109RICASUN0019443UFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI PSICOLOGIA16 CONS 1034 16 VS 1304 UFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI PSICOLOGIAIT-CE0119VS1304CONS 1034caEtà di mezzo1427789UNICAMPANIA04314nam 22006375 450 991084548610332120250807145629.09789819704484981970448010.1007/978-981-97-0448-4(MiAaPQ)EBC31221972(Au-PeEL)EBL31221972(DE-He213)978-981-97-0448-4(CKB)30995669800041(OCoLC)1427666886(EXLCZ)993099566980004120240319d2024 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierData Analytics and Machine Learning Navigating the Big Data Landscape /edited by Pushpa Singh, Asha Rani Mishra, Payal Garg1st ed. 2024.Singapore :Springer Nature Singapore :Imprint: Springer,2024.1 online resource (357 pages)Studies in Big Data,2197-6511 ;1459789819704477 9819704472 Chapter 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.This 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.Studies in Big Data,2197-6511 ;145Quantitative researchMachine learningNatural language processing (Computer science)Data Analysis and Big DataMachine LearningNatural Language Processing (NLP)Quantitative research.Machine learning.Natural language processing (Computer science)Data Analysis and Big Data.Machine Learning.Natural Language Processing (NLP).001.422005.7Singh Pushpa1734219Mishra Asha Rani1734220Garg Payal1734221MiAaPQMiAaPQMiAaPQBOOK9910845486103321Data Analytics and Machine Learning4150852UNINA