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Annotation is a process used in supervised machine learning for training data sets to help machines understand and recognize the input data and act accordingly. Labeling is used to identify key features present in the data while minimizing human involvement.

The definition of an annotation is an added note that explains something in a text. The definition of an archaic term in the Bible, listed on the bottom of the page, is an example of an annotation.

Annotating a Textclearly identify where in the text important ideas and information are located.express the main ideas of a text.trace the development of ideas/arguments throughout a text.introduce a few of the reader's thoughts and reactions.

Data annotation is the process of labeling the data available in various formats like text, video or images. For supervised machine learning labeled data sets are required, so that machine can easily and clearly understand the input patterns.

An annotation may include the following information:A brief summary of the source.The source's strengths and weaknesses.Its conclusions.Why the source is relevant in your field of study.Its relationships to other studies in the field.An evaluation of the research methodology (if applicable)More items...?Nov 16, 2021

What is Annotating? Annotating is any action that deliberately interacts with a text to enhance the reader's understanding of, recall of, and reaction to the text. Sometimes called "close reading," annotating usually involves highlighting or underlining key pieces of text and making notes in the margins of the text.

Data annotation is the technique through which we label data so as to make objects recognizable by machines. Data labeling is all about adding more info/metadata to various data. types (text, audio, image and video) in order to train ML models.