Singular Value Decomposition : Data Science Basics

So ... what is the SVD and why is it so useful for data science?

**Note** : At 4:06 I meant to say "since all the u vectors are orthogonal to each other, the U'U=I is true". Linearly independent columns alone don't guarantee this property.

[VR-fhim]

I looked all over for SVD for 3 hours, and your video in 10 minutes explained it, so nicely. Thanks.

[JD-jlyy]

You have a gift for explaining things clearly! This is so much better than the 5 SVD videos I watched prior to this haha

[saidisha]

Just amazing explanation. I had a blurry understanding of svd after taking a class and your video made the concept absolutely clear for me. Thanks a lot.

[SLopez]

Been watching your videos for months now. Very much enjoy how general your videos can be for someone outside of data science. I generally like watching math videos from non-math educators because they have a great balance of an explanation.
One thing I really enjoy about your videos is at the end you bring it back to your field and why this is useful in your world.
Reduced in entries for storage or for further calculations is very tangible to see the real world application.

[EdouardCarvalho]

Absolutely love your videos! Just to clear possible confusion for learners at 4:05 abt VtV=I because of orthonormality, not merely independence which is only a consequence. Great job!

[subandhu]

I think this video is amazing. I have been wanting to watch videos of this channel since the past 2 years but never could because i lacked the basic knowledge to gain from the explanations here. I was taught this concept in class very poorly, i immediately knew i could finally come here. The way this ties in with pca, if i am correct and the ease with which the mathematical kinks were explained was phenomenal. Glad to finally benefit from this channel. Thanks a ton.

[SupremeChickenx]

bros who make youtube math tutorials are the real MVPs

[chunchen]

I really like your videos! 👍 Methods are very clearly and concisely explained, explaining the applications of the methods in the end also helps a lot to remember what it really does. The time span of the video is also perfect! Thanks and hope to see more videos from you

[scorpio]

Thank you. Short video that packs all the right punches.

[TrangTran-dwvw]

Until you learn PCA and revisit this video, everything really makes sense!!

[amritpalsingh]

I was struggling to understand the concept in the class and this video made it very clear for me. Thank you so much. Keep them coming :)

[bittukumar-rvrx]

Thanks man for posting! Loved the explanation!

[haiderali-wrmu]

Your explained most important things about SVD. Thank you

[hamade]

I like this explanation too, thank you. Wish I had discovered you earlier during my data analysis course, but oh well :P

[rugahun]

I am glad of the note about 4:06, I freaked out when that was said. GREAT VIDEO!!

[AkshayRakate]

Thanks so much for clearing the concepts. now I can connect the dots for what's the reason we use SVD in recommended systems. 👍

[jonasngyf]

The columns of M, before SVD, could mean features. Do the columns of U and V (the left and right singular vectors) carry any physical meaning? The video keeps two singular values. How many do people usually keep?

[hameddadgour]

Wow, now I have a real appreciation for SVD :)

[msrizal]

Thanks ritvik, I'm phd candidate from Malaysia. Your videos are helping me a lot.

[nujelnigsns]

I was really struggling with leaner algebra, your video's are really a saviour