Uniform Manifold Approximation and Projection (UMAP) | Dimensionality Reduction Techniques (5/5)

[@LibertyEater]

BEST DIMENSIONAL REDUCTION VIDEO SERIES EVER! You are the 3blue1brown for data mining.

[@DeepFindr]

Thanks for the nice words!

[@jamiebernardin8561]

This is so well done it’s insane. Big thanks!

[@Tomas-p7k9p]

your videos are a goldmine :)

[@radames09]

I loved the video, my friend. Huge explanation on the topic. I'll certainly watch the other videos in a near future. Thank you

[@brunotagna4220]

Your videos are great, super high quality and clear explanations. Thanks you so much!

[@Theo-iz5cj]

Great explanation! Thank you

[@brenner4426]

you are a true hero

[@giulliabraga9709]

I just discovered your channel and THANK YOU!!

[@kevon217]

Excellent overview. Appreciate it!

[@alivecoding4995]

A great video as usual. Very detailed and comprehensive 😊. Only one thing left me confused: Why isn’t it a problem to making use of Euclidian distance in t-SNE and Umap? You could have assumed they skip it completely.

[@AppleOrPc]

Perfect! Just in time for my ML final lmao

[@DeepFindr]

Haha awesome! Good luck :)

[@Wilkshot]

Excellent.