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Spark for Data Science

Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0

Paid access
|Sep 2025
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Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0

Key Features

  • Perform data analysis and build predictive models on huge datasets that leverage Apache Spark
  • Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenges
  • Work through practical examples on real-world problems with sample code snippets

Book Description

This is the era of Big Data. The words ‘Big Data’ implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages.
Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R.
With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects.

What you will learn

  • Consolidate, clean, and transform your data acquired from various data sources
  • Perform statistical analysis of data to find hidden insights
  • Explore graphical techniques to see what your data looks like
  • Use machine learning techniques to build predictive models
  • Build scalable data products and solutions
  • Start programming using the RDD, DataFrame and Dataset APIs
  • Become an expert by improving your data analytical skills

Who this book is for

This book is for anyone who wants to leverage Apache Spark for data science and machine learning. If you are a technologist who wants to expand your knowledge to perform data science operations in Spark, or a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data Analytics, this book is for you!

Table of Contents

  1. Big Data and Data Science - An introduction
  2. Spark Programming Model
  3. Introduction to DataFrames
  4. Unified Data Access
  5. Data Analysis on Spark
  6. Machine Learning
  7. Extending Spark with SparkR
  8. Analyzing Unstructured Data
  9. Visualizing Big Data
  10. Putting it all together
  11. Building Data Science applications
https://github.com/packtpublishing/spark-for-data-science
PDF ISBN: 978-1-78588-477-1
Publisher: Packt Publishing Limited
Copyright owner: © 2016 Packt Publishing Limited
Publication date: 2025
Language: English
Pages: 344