Singular Value Decomposition (SVD): Dominant Correlations

This lectures discusses how the SVD captures dominant correlations in a matrix of data.

These lectures follow Chapter 1 from: "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz

This video was produced at the University of Washington

[capsbr]

I cannot put in words how much talent you have for teaching. It is just impressive. Thank you so much.

[seungyunsong]

If they had a Nobel prize for teaching on Youtube, this guy would be one of the top contenders

[SorenS_]

You do these fantastic explanations with your original behind-the-whiteboard technique AND you're giving the book this information comes from for free?

What a gift you are to the internet, thank you so very much. I love your teaching style.

[silvadaniloc]

This guy is the refreshed version of professor Gilbert Strang. Professor Steve Brunton, you're an amazing linear algebra teacher. Glad I found these videos. Going to recommend to my entire computational linear algebra classmates.
Thank you so much

[katherinhuang]

I learned SVD 4 years ago, and nobody ever explained it so well! Will recommend this series to every math student!

[ArkaRoychoudhury]

Steve, both Professorr Kutz and you have been helping me immensely. I have not found more concise lectures on this subject.

[zichendu]

OMG.... These videos really moved me. I haven't had the feeling to learn knowledge with excitement and refreshment, thank you so much for being such a good teacher. I feel the beauty of math.

[poiuwnwang]

Professor Brunton is great. I saw his SVD slightly covered in his in-class lecture. Now he dedicate his time to make this video lecture. Super!

[Harish-oudy]

Every one is applauding the wonderful lesson, which is very true!!

BUT No one is applauding Steve's wonderful ability to write inverted.

[jameswalters]

Engaged delivery with exceptional content clarity. If Mr Brunton isn't tenured it would be an indictment of the US university system. Cheer!

[iheavense]

Usually some of the explanations can be skipped using Einstein notation but it is often ignored how very educational it can be to explicitly walk though the process. Respect!

[Al-oyle]

a real genius can dissect complex subject matter to explain it in a simple and intuitive way. and this guy is just a splendid example of such genius

[winstonong]

This is mind-blowing. Everything falls into place nicely - the fact that the row and column correlation matrices are symmetric positive semi-definite matrices, giving rise to real positive eigenvalues and orthogonal eigenvectors, which makes the prior assumption that the singular values are real and positive, and that U and V comprise orthogonal column vectors, all true!

[ethan]

I'm highly critical of so-called YouTube "educators." I just watched several on SVD from MIT and Stanford, all of which were garbage. But this... this is art in its purest form. You are a scholar among scholars! Absolutely beautiful to watch unfold. Thank you!!!

[sundaynyanabo]

This is one of the best Stuffz I've seen on the and was taught with so much passion, rigor, Aggressiveness in presentation, clear intuition etc. With these stepwise approach, even the blind is set and equipped to be a Genius and solve real time problems. You don't want to know how grateful I am. Thanks

[invinity]

One of the best things to have happen in Jan 2020 is seeing you share more of your knowledge! Much Appreciated!

[ayankashyap]

this series is like a gift, thank you so much. Will definitely buy the book when I can :)

[somdubey]

I don't think I would ever see this sort of intuitive explanation of U and V matrices in terms of Eigen values and Eigen vectors. Thanks a lot Professor for helping humanity in understanding SVD.

[victoriaborjas]

One of the best YOUTUBE explanation i have ever seen.

[JohnSmith-oksn]

Sir, do you even have a slightest idea what a superawesomely-superawesome teacher you are?!!!

Thank you, SO MUCH!

🙏🙏🙏