From the course: MLOps Essentials: Model Development and Integration
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Creating data labels
From the course: MLOps Essentials: Model Development and Integration
Creating data labels
- [Instructor] Data labeling as an activity has gained a lot of traction lately, where a set of companies are offering this service while other companies are building software for this purpose. What is labeling? Data labeling or annotation is the process of adding contextual tags that are labels for training data that can then be used as targets for machine learning. For example, let's look at a review for a movie by John. A labeling task for this review would be about adding multiple contextual labels for this review. For example, a label called sentiment can be given a value positive. A rating label can be given a value 4.5. These labels can then be used as targets for building classification models, like, say, sentiment analysis or ratings prediction. Why is labeling gaining importance? Raw training data acquired from sources may not have prepopulated labels. Generally, structured data will contain labels, but…
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