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1
Introduction and Speaker Background
2
Understanding OCR: Basics and Importance
3
Combining OCR with LLMs for Structured Data
4
Demo Setup: Building the Application
5
Implementing OCR with Tesseract.js
6
Integrating OpenAI for Data Structuring
7
Final Testing and Conclusion
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Learn how to extract and structure data from images by combining Optical Character Recognition (OCR) and Large Language Models in this conference talk from Conf42 Prompt Engineering 2024. Explore the fundamentals of OCR technology and its significance in modern data processing, followed by practical demonstrations on integrating OCR with LLMs. Follow along with a hands-on demo that showcases building an application using Tesseract.js for OCR implementation and leveraging OpenAI's capabilities for data structuring. Master the complete workflow from initial setup through final testing, gaining practical insights into creating efficient systems for automated data extraction from visual content.

Extracting Structured Data from Images with OCR and LLM

Conf42
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