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Module

Text analytics for email routing

Archived

3 Rubriques

35 mins

Visible par : All users Applies to: Pega Customer Decision Hub 8.7, Pega Customer Decision Hub 8.6
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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.

Débutant
Anglais

Après avoir terminé ce module, vous pourrez :

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

Appliquez ce que vous avez appris dans le Défi suivant :

Training a topic model to improve email routing v3

Disponible dans les missions suivantes :

Data Scientist v4 Pega NLP Essentials v1

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