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This course is part of these tracks:

Ted Kwartler
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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  • Nick Carchedi

    Nick Carchedi

  • Tom Jeon

    Tom Jeon

  • Jeff Paadre

    Jeff Paadre

Course Description

It is estimated that over 70% of potentially useable business information is unstructured, often in the form of text data. Text mining provides a collection of techniques that allow us to derive actionable insights from these 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. Then, 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.

  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.

  3. Adding to your tm skills

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

  4. Battle of the tech giants for talent

    This chapter ties everything together with a case study in text mining for HR analytics.