Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
Spark for Data Science

You're reading from   Spark for Data Science Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0

Arrow left icon
Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781785885655
Length 344 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
 Duvvuri Duvvuri
Author Profile Icon Duvvuri
Duvvuri
 Singhal Singhal
Author Profile Icon Singhal
Singhal
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Spark for Data Science
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Big Data and Data Science – An Introduction FREE CHAPTER 2. The 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

Chapter 8.  Analyzing Unstructured Data

In this Big Data era, the proliferation of unstructured data is overwhelming. Numerous methods such as data mining, Natural Language Processing (NLP), information retrieval, and so on, exist for analyzing unstructured data. Due to the rapid growth of unstructured data in all kinds of businesses, scalable solutions have become the need of the hour. Apache Spark is equipped with out of the box algorithms for text analytics, and it also supports custom development of algorithms that are not available by default.

In the previous chapter we have shown how SparkR, an R API to Spark for R programmers can harness the power of Spark, without learning a new language .  In this chapter, we are going to step into a whole new dimension and explore algorithms and techniques to extract information out of unstructured data by leveraging Spark.

As a prerequisite for this chapter, a basic understanding of programming in Python or Scala and an overall understanding...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime
Visually different images