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Labeling Your Data

Label your data

Labeling (also known as annotating) refers to the process of adding one or more relevant tags, or keywords—usually referred to as concepts—that best describe the state of your inputs.

For example, annotations might indicate whether an image contains a jogger or a cyclist, which words were spoken in a recorded audio file, or if a concrete block contains cracks.

Successfully labeling data is a key ingredient to any custom AI solution. You can use a concept to annotate an input if that input has that entity. That’s how you prepare training data to teach your models to recognize new concepts.

After training your model using the annotated concepts, the model can learn to recognize them when it encounters data without those tags.

Clarifai Labeler offers custom tools for labeling image and video datasets, and helps you delegate and manage labeling projects of any size.

Data Labeling Services

Clarifai offers fully managed data annotation services for creating high-quality training datasets. Scale your AI initiatives quickly with high-quality, human-annotated data. You can find out more here.