Text Mining with Bag-of-Words in R
Learn the bag of words technique for text mining with R.
- 4 hours
- 15 Videos
- 69 Exercises
- 33,495 Participants
- 5,700 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.
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1
Jumping into text mining with bag of words
FreeIn this chapter, you'll learn the basics of using the bag of words method for analyzing text data.
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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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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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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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1
Jumping into text mining with bag of words
FreeIn this chapter, you'll learn the basics of using the bag of words method for analyzing text data.
-
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.
-
Adding to your tm skills
In this chapter, you'll learn more basic text mining techniques based on the bag of words method.
-
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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Lloyd's Banking Group
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Harvard Business School
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Ronald Bowers
Decision Science Analytics @ USAA
Ted Kwartler
Senior Director, Data Scientist at Liberty Mutual
Ted started his text mining journey at Amazon when he launched the social media customer service team. Since then, he has held analytical leadership roles at startups and Fortune 100 companies. He is the Author of "Text Mining in Practice with R" available at Amazon.
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Collaborators
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Nick Carchedi
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Tom Jeon
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Jeff Paadre