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Data Analytics and Machine Learning Navigating the Big Data Landscape

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 strateg...

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Bibliographic Details
Other Authors: Singh, Pushpa (Editor), Mishra, Asha Rani (Editor), Garg, Payal (Editor)
Format: eBook
Language:English
Published: Singapore Springer Nature Singapore 2024, 2024
Edition:1st ed. 2024
Series:Studies in Big Data
Subjects:
Machine Learning
Data Analysis And Big Data
Quantitative Research
Natural Language Processing (nlp)
Natural Language Processing (computer Science)
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 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

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