One of the main concerns we hear from ML engineers is that they’re spending too much time labeling low-value data that doesn’t improve model performance.
Watch our hands-on session with Labelbox Machine Learning Engineer Matt Sokoloff and Product Manager Gareth Jones to learn best practices that lift model performance faster, as well as practical tips on how to:
Use the Labelbox SDK to structure active learning workflows combining model-assisted labeling, Model Diagnostics, and embeddings so you can spend less time labeling low-value data.
Use model-assisted labeling to pre-label data with your own model, saving you time and associated cost.
Visualize model performance by comparing model predictions to ground truth labels with Model Diagnostics.
Generate embeddings from your own model to visualize similar data with the embedding projector view.
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Just some of companies that Labelbox is working with to build AI applications:
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Gareth Jones
Product Manager, Labelbox
Featured Speakers
Matt Sokoloff
Machine Learning Engineer, Labelbox
How to improve performance through active learning
Just some of companies that Labelbox is working with to build AI applications:
Copyright 2021 - All Rights Reserved.
Privacy FAQ | Privacy Notice | Cookie Notice | CCPA Notice | Terms of Use
