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Text Mining with Bag-of-Words in R
4.8(138)44k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate course guides learners through transforming unstructured text into structured analytical insights using the bag-of-words model in R. It blends text preprocessing, visualization techniques, and a real-world case study analyzing tech company employee reviews.
Who It's For
R analysts and data scientists looking to extract actionable business intelligence from unstructured text data and reviews.
Key Takeaways
- Bag-of-Words Method: Learn how to tokenize, clean, and structure text into term frequency matrices for analysis.
- Text Visualization: Create informative visual summaries of text corpora to highlight key themes and word patterns.
- Case Study Application: Apply text mining techniques to real-world tech employee reviews to uncover business insights.
About this course
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.
Price
Free
This course is free to enrol.
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