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Hands-On Data Analysis with Scala

You're reading from   Hands-On Data Analysis with Scala Perform data collection, processing, manipulation, and visualization with Scala

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789346114
Length 298 pages
Edition 1st Edition
Languages
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Author (1):
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Rajesh Gupta Rajesh Gupta
Author Profile Icon Rajesh Gupta
Rajesh Gupta
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Toc

Table of Contents (14) Chapters Close

Preface 1. Section 1: Scala and Data Analysis Life Cycle FREE CHAPTER
2. Scala Overview 3. Data Analysis Life Cycle 4. Data Ingestion 5. Data Exploration and Visualization 6. Applying Statistics and Hypothesis Testing 7. Section 2: Advanced Data Analysis and Machine Learning
8. Introduction to Spark for Distributed Data Analysis 9. Traditional Machine Learning for Data Analysis 10. Section 3: Real-Time Data Analysis and Scalability
11. Near Real-Time Data Analysis Using Streaming 12. Working with Data at Scale 13. Another Book You May Enjoy

ML overview

Let's first look at what ML is. In a traditional sense, in order to solve a computational problem, we typically write explicit computer instructions that solve the problem based on all of the possible scenarios. The assumption here is that all of the rules associated with the specific problem being solved are known and well-defined in advance and could be codified into computer instructions. This assumption, however, is not always true. There are times when the rules are not known in advance and it is impractical to define deterministic rules that could be applied to solve the problem.

Let's look at this problem using a concrete example of an app stores where a consumer has the option of buying an app from a fairly large catalog of available apps. When the consumer logs into the app store, it displays a set of recommended apps that the consumer is highly...

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