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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

Natural language processing for data analysis

Natural language processing (NLP) is the ability of a machine to analyze and understand human language. Human language has a very high amount of complexity, which makes parsing and understanding it difficult. There is a great deal of context in spoken and written language. Machines work well with precise rules that are within the confines of good context. With that said, it is still possible to gain an insight into text analysis using NLP techniques. An excellent example of this is Twitter sentiment analysis. Based on the contents of tweets, using NLP, it is possible to determine whether the sentiments of the people are generally positive or negative as a group. Another great example is the successful application of NLP techniques in analyzing customer reviews of a product or service.

The ML algorithms explored so far in this chapter...

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