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.
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.
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.
