Man! As a layman that I am (indeed I was) on the subject, I now feel rich with knowledge about it. Thank you, Professor Kutz, for your generosity!

Amazing video, best explanantion so far including my own lecturer. I appreciated the few snippets of code as well.

Thank you superhandsome, presidential Jason Bourne for this lecture. You look similar to Nathan Kutz, BTW.

I work as an ic designer and because of work I am trying real hard to understand some complicated paper that involve floquet theory and come across ur channel, I definitely learned matrix and Eigenvector in college which I forgot, this blows my mind. Thank you

great explanation on the topic! it helped me a lot :)

Thank you Nathan

Thank you for the wonderful lecture sir

Thank you for your wonderful lecture, it really helped me understand what are eigenfaces. I do have one doubt - at 28:30 when you talk about taking a new image of Margaret Thatcher, and project it on the 20 eigen images, what do the bar graphs in the right most represent?

How do you form the projections on eigenvectors? Do you use python or some other programs to construct those projections? if so please let me know the code of these functions. I would be very grateful.

Nathan Kutz is the best

I could not find the code on the link provided. Can someone help me with this?

Nice video! However, C isn't the correlation matrix containing the correlations between the images, but the correlations between pixels (since C is a 120*80-by-120*80 matrix, not a 20-by-20 matrix).