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Scala and Spark for Big Data Analytics

You're reading from  Scala and Spark for Big Data Analytics

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781785280849
Pages 796 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Md. Rezaul Karim Md. Rezaul Karim
Profile icon Md. Rezaul Karim
Sridhar Alla Sridhar Alla
Profile icon Sridhar Alla
View More author details

Table of Contents (19) Chapters

Preface Introduction to Scala Object-Oriented Scala Functional Programming Concepts Collection APIs Tackle Big Data – Spark Comes to the Party Start Working with Spark – REPL and RDDs Special RDD Operations Introduce a Little Structure - Spark SQL Stream Me Up, Scotty - Spark Streaming Everything is Connected - GraphX Learning Machine Learning - Spark MLlib and Spark ML My Name is Bayes, Naive Bayes Time to Put Some Order - Cluster Your Data with Spark MLlib Text Analytics Using Spark ML Spark Tuning Time to Go to ClusterLand - Deploying Spark on a Cluster Testing and Debugging Spark PySpark and SparkR

Unsupervised learning

In this section, we will provide a brief introduction to unsupervised machine learning technique with appropriate examples. Let's start the discussion with a practical example. Suppose you have a large collection of not-pirated-totally-legal mp3s in a crowded and massive folder on your hard drive. Now, what if you can build a predictive model that helps automatically group together similar songs and organize them into your favorite categories such as country, rap, rock, and so on. This act of assigning an item to a group such that a mp3 to is added to the respective playlist in an unsupervised way. In the previous chapters, we assumed you're given a training dataset of correctly labeled data. Unfortunately, we don't always have that extravagance when we collect data in the real-world. For example, suppose we would like to divide up a large...

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