n the last chapter, we talked about intent classification: building ML systems that can recognize the meaning (the intention) of text. We talked about one common use of intent classification, which is to build smart assistants that can understand what we’re telling them and carry out our commands.
In this chapter, we’ll look at how ML models that understand the meaning of text can be used to build question answering (QA) systems. QA systems recognize and respond to our questions, discovering the answers automatically from a set ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.
n the last chapter, we talked about intent classification: building ML systems that can recognize the meaning (the intention) of text. We talked about one common use of intent classification, which is to build smart assistants that can understand what we’re telling them and carry out our commands.