Discover Ways of Training ML Models for Document Data Extraction
Machine learning models help us extract data from semi-structured documents. Let's learn how...
Document processing sometimes requires machine learning models to classify and extract the data we need. If someone wonders whether we need ML models all the time, the answer is no. We do not need machine learning models all the time to extract data. However, some scenarios require ML models to perform the data extraction. For example, we don't need any machine learning models to extract data from structured documents. However, we may need machine learning for semi-structured documents such as invoices or unstructured documents such as legal documents. The reason is that the document does not follow a specific structure, and there can be various ways of representing the data in documents.
Given such situations, it is crucial to know how to train Document Understanding models according to our needs and the best practices that we need to follow to build models with high accuracy rates. Furthermore, machine learning is not a one-time task. The learning has to continue every day automatically to enhance the prediction accuracy.
This tutorial covers each step in training Document Understanding models and discusses the best practices we need to follow.