- Creating a word cloud
- Analyzing sentiment
- Extracting emotions from text
- Clustering similar entities based on text
- Using classification for supervised learning
- Recommending items to users based on text data analytics
Skill Level Intermediate
- Businesses want to understand customer sentiment, predict customer value, and provide valuable services. One approach in doing this is to mine data generated by customers. Today, more and more of this data is generated in text form through social media, emails, blogs, and text messages. Mining text data is not a trivial task. It is typically done via machine learning, which requires a special set of tools and techniques. My name is Kumaran Ponnambalam. In this course, I will show you the tools and techniques available for text analytics and predictions in R. We will use popular text processing packages in R to build use cases in R Studio. You need prior familiarity with R, R Studio, and machine learning. That being said, let's explore how to do text analytics and machine learning in R.
Predictive Customer Analyticswith Kumaran Ponnambalam1h 37m Intermediate
1. Word Cloud
2. Sentiment Analysis
5. Predictive Text
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.