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About this event
This workshop is part of our Getting Started with Voxel51 monthly series — a recurring session designed to help you build a strong foundation in data-centric AI workflows.
👉 Register to get access to this session and its companion Advanced Voxel51 session.
In this session, you’ll learn how to manage large-scale computer vision datasets using Voxel51. 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.
Resources
Host
What you’ll learn:
- Structure unstructured data into queryable schemas (images, video, point clouds)
- Query datasets using the Voxel51 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 Voxel51 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
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