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Description

Large language models (LLMs) are becoming increasingly powerful and versatile, but their ability to process unstructured data remains a challenge. Extracting, transforming and loading (ETL) unstructured data into a format that LLMs can understand is a complex and time-consuming process. In this workshop, we will demonstrate an ETL solution in Python using the unstructured library to process different unstructured data formats that can be inputs to LLMs. The workshop will cover the following topics: * The challenges of ETL of unstructured data for LLMs * Case study of how to use the ETL solution to load, transform and prepare unstructured data in different formats (PDF, CSV, HTML, PPTX). * Possible use cases of the ETL solution for LLMs * Question Space.