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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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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

Using ML to learn from data

ML is the process of discovering patterns in data without explicitly programming the logic. In this section, we will look at how ML can be performed using Scala. This is a very vast topic in itself, so we will only look at this from an applied usage point of view.

Smile (https://haifengl.github.io/smile/index.html) is a popular Scala library that helps with ML-related tasks. There are many other Scala ML libraries that are extremely popular, such as Spark MLlib; however, these libraries are more suitable for distributed processing environments. We will look at these in subsequent chapters.

Setting up Smile

There are multiple ways to set up Smile on your machine. Refer to Smile Quick Start at https...

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