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Version: 2.0

Introduction to Annotation


What is annotation?

Annotation is the process of assigning tags to data in order to train a machine learning model. Annotations turn unstructured data into information that can used to gain informed insights and extract useful information that can be further analyzed.

What are annotations used for?

Annotations have multiple applications in regards to transforming your data into information. You can use annotations to analyze data as well as help a machine learning (or Artificial Intelligence) model to train.

Key concepts of annotation

Annotation is divided into two main processes. Text classification and text structuration. Each is used to transform unstructured data into information. In this video series your will delve deeper into both of these processes as well as their corresponding components to better understand how annotation works and extract useful insights from your data.