PluralSight – Fact Verification with RAGs
English | Tutorial | Size: 105.36 MB
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.
RAPIDGATOR:
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TURBOBIT:
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