This workshop is part of our Getting Started with FiftyOne monthly series — a recurring session designed to help you build a strong foundation in data-centric AI workflows.
Time, Place and Location
July 1, 2026
9 AM PST – 10 AM PST
Online. Register for the Zoom!
In this session, you’ll learn how to manage large-scale computer vision datasets using open source FiftyOne. We’ll cover how to curate, visualize, and evaluate your data and models — with a focus on improving data quality over brute-force model iteration.
You’ll walk away with a repeatable framework for building data-centric AI pipelines across research and production.
What you’ll learn:
- Structure unstructured data into queryable schemas (images, video, point clouds)
- Query datasets using the FiftyOne SDK with filters, tags, and confidence thresholds
- Visualize high-dimensional embeddings to identify clusters, gaps, and outliers
- Automate data curation and prioritize high-value samples for labeling
- Debug model performance using evaluation tools (confusion matrices, PR curves)
- Customize FiftyOne with dashboards and interactive panels
Prerequisites:
- Working knowledge of Python
- Familiarity with machine learning and/or computer vision fundamentals
