Getting Started with FiftyOne Workshop
January 31, 2024 at 9 AM Pacific / 12 PM Eastern
When
January 31, 2024 at 9 AM Pacific / 12 PM Eastern for 90 mins
Where
Virtual / Zoom
Abstract
Want greater visibility into the quality of your computer vision datasets and models? Then join Leila Kaneda, customer-facing Machine Learning Engineer at Voxel51, for this free 90 minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.
In the first part of the workshop we’ll cover:
FiftyOne Basics (terms, architecture, installation, and general usage)
An overview of useful workflows to explore, understand, and curate your data
How FiftyOne represents and semantically slices unstructured computer vision data
The second half will be a hands-on introduction to FiftyOne, where you will learn how to:
Load datasets from the FiftyOne Dataset Zoo
Navigate the FiftyOne App
Programmatically inspect attributes of a dataset
Add new sample and custom attributes to a dataset
Generate and evaluate model predictions
Save insightful views into the data
Prerequisites are a working knowledge of python and basic computer vision. All attendees will get access to the tutorials, videos, and code examples used in the workshop.
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About the Instructor
Leila Kaneda is a customer-facing Machine Learning Engineer at Voxel51, where she focuses on helping researchers and engineers understand how visualizing and analyzing their data will lead them down the path of understanding and solving some of their domain’s hardest problems. With an extensive background in education, community building, and leadership, Leila is passionate about simplifying and sharing information in a way that is practical and engaging across a variety of different audiences. In her free time, Leila is a keynote speaker and serves on boards supporting industry connections with STEM education in rural areas. Prior to joining Voxel51, Leila worked for startups, small, and large companies helping them understand the best ways to leverage machine learning to solve domain-specific problems.