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Preparing your journey
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Interactive Learning
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Preparing your journey
Quantato
Interactive Learning
PCA
VS
t-SNE & UMAP
PCA is a linear method preserving global variance, while t-SNE is non-linear and excels at preserving local cluster structure for visualization.
Need linear dimensionality reduction
Want to preserve global structure
Need interpretable components
Preprocessing for other algorithms
Visualizing high-dimensional data
Finding clusters or patterns
Local structure matters more
Exploratory data analysis
PCA
t-SNE & UMAP
Interactive lessons with visualizations and hands-on practice