Mastering Spark for Data Science

Master the techniques and sophisticated analytics used to construct Spark based solutions that scale to deliver production grade data science products

Mastering Spark for Data Science

Mastering
Andrew Morgan et al.

Master the techniques and sophisticated analytics used to construct Spark based solutions that scale to deliver production grade data science products
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Book Details

ISBN 139781785882142
Paperback541 pages

Book Description

Data science seeks to transform the world using data and this is typically achieved through disrupting and changing real processes in real industries. In order to operate at this level you need to be able to build data science solutions of substance – solutions that solve real problems and that run so relialbly that people trust and actualize them. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs.

This book deep dives into Spark to deliver production grade data science solutions that are innovative, disruptive, and reliable. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights. You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries including: Spark SQL, visual streaming, MLlib, and more.

You will be introduced to advanced techniques and methods that will help you build data science solutions and you’ll be shown how to construct commercial grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, sophisticated data science methods, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly.

Table of Contents

What You Will Learn

  • Learn the design patterns that integrate Spark into industrialized data science pipelines
  • See how commercial data scientists design scalable code and reusable code for data science services
  • Explore cutting edge data science methods so that you can study trends and causality
  • Find out how Spark can be used as a universal ingestion engine tool and as a web scraper
  • Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining
  • Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams
  • Study advanced Spark concepts, as well as solution design patterns and integration architectures
  • Demonstrate powerful data science pipelines
  • Receive detailed guidance on how to run Spark in production

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Table of Contents

Book Details

ISBN 139781785882142
Paperback541 pages
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