Essentials of Big Data Analytics
eBook - ePub

Essentials of Big Data Analytics

Applications in R and Python

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Essentials of Big Data Analytics

Applications in R and Python

About this book

Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments. - Includes hands-on Tutorials and Case Studies: Structured exercises and real-world examples reinforce learning and skill-building - Focuses on Python and R for Big Data: Detailed lessons in Python and R programming cater to the increasing demand for data science expertise - Balanced Theory and Practice: Comprehensive coverage ensures a strong theoretical foundation paired with actionable insights for real-world application

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Information

Publisher
Morgan Kaufmann
Year
2026
eBook ISBN
9780443452079
Topic
Informatica
Subtopic
Intelligenza artificiale (IA) e semantica

Table of contents

  1. Title of Book
  2. Chapter 1: Introduction to big data analytics
  3. Chapter 2: Mathematical foundations
  4. Chapter 3: Big data technologies and programming
  5. Chapter 4: Data ingestion and preprocessing
  6. Chapter 5: Big data storage and management
  7. Chapter 6: Advanced MapReduce for big data processing
  8. Chapter 7: Machine learning techniques for big data processing
  9. Chapter 8: Mining data streams
  10. Chapter 9: Case studies and practical applications
  11. Chapter 10: Hands-on exercises and tutorials with R, Python and MapReduce
  12. Chapter 11: Emerging trends and future directions
  13. Nomenclature
  14. Glossary
  15. Features of the book
  16. Index

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Yes, you can access Essentials of Big Data Analytics by Pallavi Chavan,Kalyani Pampattiwar,Ramchandra Mangrulkar in PDF and/or ePUB format, as well as other popular books in Informatica & Intelligenza artificiale (IA) e semantica. We have over one million books available in our catalogue for you to explore.