Automate the Boring Stuff With Large Language Models
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Learn how to automate repetitive tasks using Large Language Models (LLMs). Streamline workflows, create bots, and enhance productivity with AI-driven automation.
At a Glance
Learn how to use Large Language Models (LLMs) to get more done in less time. Increase efficiency by automating boring, redundant tasks! In this guided project, you will learn how to use LLMs to cover more ground with just a bit of Python code.
As an industry use case example, we will take on the role of a manager at a call center who wants to review call transcripts and produce feedback for agents that have fallen below expectations.
While this is one specific use case, the same idea may be extended to countless applications!
A Look at the Project Ahead
- The capabilities and general use cases of LLMs
- How to interact with LLMs using the IBM Watson Python API
- How to use LLMs to solve otherwise long and boring tasks
- How to scale our solutions
What You’ll Need
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