Text Mining with Bag-of-Words in R

Learn the bag of words technique for text mining with R.
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4 Hours15 Videos69 Exercises38,678 Learners
5700 XP

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Course Description

It is estimated that over 70% of potentially usable business information is unstructured, often in the form of text data. Text mining provides a collection of techniques that allows us to derive actionable insights from unstructured data. In this course, we explore the basics of text mining using the bag of words method. The first three chapters introduce a variety of essential topics for analyzing and visualizing text data. The final chapter allows you to apply everything you've learned in a real-world case study to extract insights from employee reviews of two major tech companies.

  1. 1

    Jumping into text mining with bag of words

    In this chapter, you'll learn the basics of using the bag of words method for analyzing text data.
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  2. 2

    Word clouds and more interesting visuals

    This chapter will teach you how to visualize text data in a way that's both informative and engaging.
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  3. 3

    Adding to your tm skills

    In this chapter, you'll learn more basic text mining techniques based on the bag of words method.
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  4. 4

    Battle of the tech giants for talent

    This chapter ties everything together with a case study in text mining for HR analytics.
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In the following tracks
Text Mining
Nick CarchediTom Jeon
Intermediate R
Ted Kwartler Headshot

Ted Kwartler

Adjunct Professor, Harvard University
Ted Kwartler is the VP, Trusted AI at DataRobot. At DataRobot, Ted sets product strategy for explainable and ethical uses of data technology in the company's application. Ted brings unique insights and experience utilizing data, business acumen and ethics to his current and previous positions at Liberty Mutual Insurance and Amazon. In addition to having 4 DataCamp courses he teaches graduate courses at the Harvard Extension School and is the author of Text Mining in Practice with R.
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