Annotation

Annotation, also known as data labeling, is the process of creating annotations or labeling of data. This is typically done with images, but can also be done with videos, audio, and text. This process has become increasingly  popular and more important with the rise of machine learning and supervised learning.

Training data that is labeled are fed through supervised learning algorithms. Although there are many labeled datasets that are public and accessible, companies usually prefer building their own proprietary annotated data sets. Data labeling software is generally used by companies to achieve these goals.

Businesses can either use a third-party services provider which connects the business with labelers or use data labeling software which provides a platform for business users to label their own data, to annotate the data. A combination of the aforementioned methods can also be used. Guidance on the most effective and efficient method are even provided by some tools. It will dynamically choose the source of annotation for any given data point.

Images, videos, audio, and text are four types of annotation. Improving business outcomes and ensuring algorithmic accuracy are benefits of annotation. Machine learning engineers and other artificial intelligence practitioners can have a full understanding of their data and its labels by using annotation.