Using Azure AI Document Intelligence to Accelerate Data Ingestion and Extraction

*About this session:*
Learn how Azure AI Document Intelligence can be used to automate the extraction of data from forms, documents, and images. In this session, we will discuss the service, how it works on both pre-defined document types as well as your own custom types, and how it can be integrated into a larger ingestion workflow, to help reduce the time and effort to get data from your users into your backend systems.
*Who is it aimed at?*
Developers, data engineers, and business users
*Why should I attend?*
If you work with processes where data is received from customers and end users in paper forms, scans, or other non-digital formats, and you struggle with getting data from there into your backend systems, this session can give you insights on how to modernize this workflow.
*Learn more about Azure AI Document Intelligence with these ressources:*
aka.ms/Apr8Azu...
aka.ms/Apr8Azu...
[eventID:22159]

[@shikhabasak4852]

Hi, I have a doubt with the result confidence part. In both extraction and classification models, how does azure set the confidence level? When did the user confirm (validate) that the information the model read and understood was correct or not, based on which the model is x% confident about the result? (I'm thinking of it in terms of y_pred and y_actual we do during model training on python using sklearn - which helps the model evaluate accuracy, recall, etc)