UMAP Dimension Reduction, Main Ideas!!!

UMAP is one of the most popular dimension-reductions algorithms and this StatQuest walks you through UMAP, one step at a time, so that you will have a solid understanding of how UMAP works. NOTE: This StatQuest is based on the original UMAP manuscript... https://arxiv.org/pdf/1802.03426.pdf ...specifically Appendix C, From t-SNE to UMAP, which is also here... https://jlmelville.github.io/uwot/uma... ...and the UMAP user documentation... https://umap-learn.readthedocs.io/en/... For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon:   / statquest   ...or... YouTube Membership:    / @statquest   ...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:   / joshuastarmer   0:00 Awesome song and introduction 1:07 Motivation for UMAP 2:55 UMAP main ideas 5:22 Calculating high-dimensional similarity scores 10:41 Getting started with the low-dimensional graph 12:37 Calculating low-dimensional similarity scores and moving points 15:49 UMAP vs t-SNE #StatQuest #UMAP #DimensionReduction