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Text analytics for email routing

2 Topics

25 mins

Visible to: All users
Beginner Pega Customer Decision Hub '23 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:

Describe practical applications where text analytics are useful.
Describe the role of machine learning in text analytics.
Explain how the system trains text predictions with classified messages.

Practice what you learned in the following Challenge:

Training a topic model to improve email routing v5

Available in the following mission:

Pega NLP Essentials v3

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