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Text analytics for email routing

3 Topics

35 mins

Visible to: All users
Beginner Pega Customer Decision Hub 8.7 Pega Customer Decision Hub 8.6 English
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Humans can effortlessly interpret a single tweet but are unable to parse a large volume of information efficiently. Businesses are exploring ways to use machine learning to extract meaningful information from a large number of text messages. Learn how a text prediction can work to detect topics, extract entities, and identity the sentiment for incoming emails.

After completing this module, you should be able to:

Explain text analytics
Describe practical applications where text analytics can be used
Describe the role of machine learning in text analytics
Explain how text predictions are trained on classified messages

Practice what you learned in the following Challenge:

Training a topic model to improve email routing v3

Available in the following missions:

Data Scientist v4 Pega NLP Essentials v1

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