From the course: Leveraging Cloud-Based Machine Learning on AWS: Real-World Applications
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What's different? - Amazon Web Services (AWS) Tutorial
From the course: Leveraging Cloud-Based Machine Learning on AWS: Real-World Applications
What's different?
- [Instructor] When you build a SageMaker model, you're going to need training data to train the model. And that's where Ground Truth comes in. Amazon's SageMaker Ground Truth allows you to build datasets that allow you to train machine learning models quickly. So the idea is to provide a single source of truth of information that goes into a model and therefore train those models better. Ultimately, this provides access to public and private human labelers and provides them with the ability to leverage workflows and interfaces for common labeling tasks. Now, keep in mind that labeling in the context of machine learning is the ability for humans or sometimes automated processes to tag information or tag images with certain labels. So we may go into a dataset and label them with their own way of labeling the data or we may have an automated process that does the same thing. And the term ground truth has an…
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