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Understanding UMAP
UMAP is a new dimensionality reduction technique that offers increased speed and better preservation of global structure.
samurairodeo 2022/01/10
“Dimensionality reduction is a powerful tool for machine learning practitioners to visualize and understand large, high dimensional datasets. One of the most widely used techniques for visualization is t-SNE, but its performance suffers with large datasets and using it correctly can be challenging
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What-If Tool
Visually probe the behavior of trained machine learning models, with minimal coding. A key challenge in developing and deploying responsible Machine Learning (ML) systems is understanding their performance across a wide range of inputs. Using WIT, you can test performance in hypothetical situations, analyze the importance of different data features, and visualize model behavior across multiple mod
samurairodeo 2019/12/09
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