ML Club Video: Dimensionality Reduction

Update: There is a new video on this topic from 2024. Please refer to the new video here as it is updated with more info.

In this ML Club session, we’ll learn how to visualize 1000-dimensional data!

High dimensional data is everywhere!

How do we do this? We have to represent a 1000 dimensions in 2 dimensions such that the meaning of the data is still preserved. In the session we talk about two very different approaches – Principal Component Analysis and t-Distributed Stochastic Neighbor Embedding.

How do these approaches work? Watch the video to find out!

Thank you to the Statquest video: https://www.youtube.com/watch?v=NEaUSP4YerM for helping me with this lecture. Highly recommend the channel!