Learn about the tools and techniques for analyzing text data in R and discover how to perform machine learning and predictions.
- 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.
Released
10/1/2019- 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
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Video: The need for text analytics