Fact Verification with RAGs
Learn how to use retrieval-augmented generation (RAG) to ensure the accuracy of AI-generated content. This course uses Python and advanced NLP models to implement data retrieval and verification systems.
What you'll learn
Ensuring the accuracy of AI-generated content is critical. In this course, Fact Verification with RAGs, you’ll learn to implement a system that verifies AI-generated content using NLP techniques. First, you’ll explore how to retrieve relevant data from a dataset using Python and the pandas library. Next, you’ll discover how to use pre-trained sentence transformers to generate embeddings for textual data. Finally, you’ll learn how to implement a zero-shot classification model to assess the veracity of claims. When you're finished with this course, you’ll have the essential skills and knowledge of retrieval-augmented generation needed to ensure the accuracy and reliability of AI-generated content using Python common libraries.
Table of contents
About the author
Eduardo is a technology enthusiast, software architect and customer success advocate. He's designed enterprise .NET solutions that extract, validate and automate critical business processes such as Accounts Payable and Mailroom solutions for all types of organizations. He's designed and supported production systems for global names such as Coca Cola, Enel, Pirelli, Fiat-Chrysler, Xerox and many others. He's a well-known specialist in the Enterprise Content Management market segment, specifically... more