Latent Space Visualisation: PCA, t-SNE, UMAP | Deep Learning Animated
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YouTubeDeepia
Latent Space Visualisation: PCA, t-SNE, UMAP | Deep Learning Animated
In this video you will learn about three very common methods for data dimensionality reduction: PCA, t-SNE and UMAP. These are especially useful when you want to visualise the latent space of an autoencoder. If you want to learn more about these techniques, here are some key papers: - UMAP: Uniform Manifold Approximation and Projection for ...
140.4K viewsAug 5, 2024
Variance Reduction Methods
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