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Last Updated: October 1, 2026
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In this video, I will give you an easy and practical explanation of Unifold Manifold Approximation and Projection ( In this video you will learn about three very common methods for data dimensionality reduction: PCA, t-SNE and If you understand the main ideas of how This talk will present a new approach to dimension reduction called High-dimensional data is everywhere — 784-pixel digits, 20000-gene cells — but you can't see it. Learn the basics about making a custom map in Papers / Resources ▭▭▭ Colab Notebook: ... In this video, we will cover the similarities and differences between PCA, t-SNE, This video describes the PaCMAP technique for dimension reduction, which is an alternative to t-SNE and Google colab link: colab.research.google.com/drive/1jV4kOHbpdu0Zc7Ml18kdxaQJxV81vB21?usp=sharing
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