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Essential PySpark for Scalable Data Analytics

You're reading from  Essential PySpark for Scalable Data Analytics

Product type Book
Published in Oct 2021
Publisher Packt
ISBN-13 9781800568877
Pages 322 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Sreeram Nudurupati Sreeram Nudurupati
Profile icon Sreeram Nudurupati
LinkedIn
Sreeram Nudurupati is a data analytics professional with years of experience in designing and optimizing data analytics pipelines at scale. He has a history of helping enterprises, as well as digital natives, build optimized analytics pipelines by using the knowledge of the organization, infrastructure environment, and current technologies.
See other products by Sreeram Nudurupati

Table of Contents (19) Chapters

Preface 1. Section 1: Data Engineering
2. Chapter 1: Distributed Computing Primer 3. Chapter 2: Data Ingestion 4. Chapter 3: Data Cleansing and Integration 5. Chapter 4: Real-Time Data Analytics 6. Section 2: Data Science
7. Chapter 5: Scalable Machine Learning with PySpark 8. Chapter 6: Feature Engineering – Extraction, Transformation, and Selection 9. Chapter 7: Supervised Machine Learning 10. Chapter 8: Unsupervised Machine Learning 11. Chapter 9: Machine Learning Life Cycle Management 12. Chapter 10: Scaling Out Single-Node Machine Learning Using PySpark 13. Section 3: Data Analysis
14. Chapter 11: Data Visualization with PySpark 15. Chapter 12: Spark SQL Primer 16. Chapter 13: Integrating External Tools with Spark SQL 17. Chapter 14: The Data Lakehouse 18. Other Books You May Enjoy

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Authors (1)

Profile icon Sreeram Nudurupati
LinkedIn
Sreeram Nudurupati is a data analytics professional with years of experience in designing and optimizing data analytics pipelines at scale. He has a history of helping enterprises, as well as digital natives, build optimized analytics pipelines by using the knowledge of the organization, infrastructure environment, and current technologies.
See other products by Sreeram Nudurupati

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