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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

Table of Contents (19) Chapters

Preface

Section 1: Data Engineering

Chapter 1: Distributed Computing Primer

Chapter 2: Data Ingestion

Chapter 3: Data Cleansing and Integration

Chapter 4: Real-Time Data Analytics

Section 2: Data Science

Chapter 5: Scalable Machine Learning with PySpark

Chapter 6: Feature Engineering – Extraction, Transformation, and Selection

Chapter 7: Supervised Machine Learning

Chapter 8: Unsupervised Machine Learning

Chapter 9: Machine Learning Life Cycle Management

Chapter 10: Scaling Out Single-Node Machine Learning Using PySpark

Section 3: Data Analysis

Chapter 11: Data Visualization with PySpark

Chapter 12: Spark SQL Primer

Chapter 13: Integrating External Tools with Spark SQL

Chapter 14: The Data Lakehouse

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Authors (1)

Sreeram Nudurupati

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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