Wading through all your unstructured data to accurately annotate assets requires a tremendous amount of patience, organization, and time. This webinar will cover six key time-saving practices implemented by leading AI teams when handling AI data. Join us to discover how to:
Annotate faster with a dynamic queueing system
Improve communication, collaboration, and consensus between teams
Utilize a programmatic-approach for quicker access to data
Leverage software optimized for speed
Incorporate automation through model-assisted labeling
Utilize active learning and prioritize the right data
We’ll also be answering live Q&A from the audience so that you can tailor these lessons into your own MLOps and accelerate your AI journey.
Just some of companies that Labelbox is working with to build AI applications:
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Rahul Sharma
Sr. Machine Learning Support Engineer,
Labelbox
Featured Speakers
6 best practices to save time when creating AI data
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
ML Unboxed: How to diagnose and improve model performance
January 12: 11am PT
January 13: 8am PT/11am ET/4pm GMT
ML UNBOXED
Mark Ghannam
Solutions Engineer, EMEA, Labelbox
Zeke Emerson
MLSE,
Labelbox