Azure AI Document Intelligence - Custom Extraction
Science & Technology
Azure AI Document Intelligence - Custom Extraction
Hello everyone, my name is Emerson, and in this article, we will delve into custom models on Azure AI Document Intelligence, specifically focusing on custom extraction models. In this walkthrough, we will explore how to create, train, and utilize custom extraction models using the Document Intelligence Studio on Azure.
To start, we will create a project and upload documents that need to be trained for extraction. We will define fields such as contract names, landlord names, and tenant names within these documents. The training process involves selecting a neural model, running the training, and then testing the model on new documents to extract the desired information with confidence values. Finally, we will explore how to use the trained model in applications by accessing the provided code snippets.
If you are interested in working with Cloud technology, especially in the realm of Azure AI Document Intelligence, this article will provide you with valuable insights on custom extraction models and how to implement them effectively.
Keyword
- Azure AI
- Document Intelligence
- Custom Extraction
- Neural Model
- Code Integration
FAQ
- How can I create a custom extraction model on Azure AI Document Intelligence?
- What are the key steps involved in training a custom extraction model?
- How can I access and utilize the trained model in my applications?
- What are the benefits of using custom models for document extraction in the cloud environment?