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.
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.ion. View more CV events here.
Host
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
Additional Notes:
All attendees will receive access to tutorials and code examples
This is a monthly recurring series — ideal for new users or those looking to level up their workflows over time