Identifying Structure in Data: All you need to know about Dimensionality Reduction, Clustering and more
Constantin Seibold
Abstract
This tutorial explores techniques for dataset curation, quality monitoring, dimensionality reduction (t-SNE, UMAP, h-NNE), and clustering (k-means, DBSCAN, FINCH). Attendees will learn how to use these methods to understand structure, reduce bias, detect outliers, and improve performance in AI and CV workflows.
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