This guy always leaves a smile on my face

You are on my elite teachers list: Sal from Khan academy, The organic chemistry tutor, Professor Dave, and now Dr Peyam. Hats off to all of you for making my university life easier. Massive respect and love for all of you

3 hrs of lecture and i didnt understand a word. 5 mins of watching this video - and i undersand every thing !! thank you.

Im at the point of the semester where I need to take whatever this guy took

Best QR decomposition video I've found. Well explained, straight to the point, easy to understand. Thank you.

You sir are a genius. This linear algebra extravaganza was super helpful!

This is the funnest math tutorial video I've ever seen. You made the process seem so streamlined and easy, thank you!

Thank you for explaining a simple topic as it should be explained, in a simple way. Great explanation!

the radiance of his positivity in his teachings make me love linear algebra XD

thank dr peyam! I really liked the extension to least squares in the second half of the video.

I have been struggling with this topic, you explained this so well. Thank you!

man how did i not find you before, you're litteraly going to make me pass numerical analysis

The best explanation given on this topic!

That's awesome. I don't understand matrix and I don't understand english but with your funny explinations, I understand everything. Thank you so much.

Thanks so much for explanation, It was clear and concise and to the point.

This was expained so well that i understood despite i talk spanish and dont know even a little of english

What a living legend... Amazing Peyam

Thank you so much. This really helped my understanding of qt decomposition

This tutorial is amazing, thank you

God Bless you, man!

Thanks a lot!! The example was very illustrating!

Thanks a lot for your clear explanation!

Great explanation, thanks!

Thanks you for an amazing explanation!

Great video man

Perfect explanation. Thx professor

WOW THANK YOU DR. YOU ARE THE BEST

I wonder... Would a left-sided RQ decomposition ever be useful? And how easy is it to generate compared to QR?

I've Always seen matrix decompositions (QR, LU) done with square matrix, it's a bit strange for me to see them in the nonsquare world. Also, I was told that Q must be Unitarian and Hermitian (I guess for IR orthogonal and symmetric would be fine) hence making QR only be possible in square matrices by definition. I wonder how much of a lie resides in what I just told

This was really good :)

thanks for your work.

thanks for the video! but one question, even if R' is not invertible (meaning A has linear dependency) , there still solution for LS right? just lose one dimension. No?

I love this man

absolutely fantastic

omg you're so cute i can watch you teach all day

Thanks alot!!!!!!!!!!!!!!!!!!!!! Prepare to hand in my homework set~~~~~~~

You're my hero!

A nice lin alg video again. I hope my students will also like it 😊

Very useful session thank you so much ❤

thank you great video

And the next decomposition should be the very important SV decomposition which one typically uses in the matrix product state formalism. :D

crazy good, thank you

Wow best explanation and nice style of teaching. Very precise and easy to understand

omg, thank you a lot for your priceless knowlage

Thank you so much. Very helpful

Foi muito útil! Thank you so much!

And I thought it was something to do with QR codes :P

Do you have videos on SVD? Thanks for this video

Thank you sir.

Thank you sir👍

THANK YOU SO SO MUCH

Hey, thanks for the amazing video. I just have one quick doubt. As you said Q is orthonormal matrix, then when I compute Q*Q' it does not give I. Please enlighten me, or am I misunderstanding something?

good job peyam

very very clear

u are like the bob ross of math :) thank you

WOW this was explained really well, I wish my professor could teach like this :(

How about its importance in finding evalues?

What is the application of QR decomposition?

thx bro !!

Great!

Thanks! Sir

Could you do QZ decomposition.

Thanks this video series has really been helpful! Also, just wondering if you would be willing to share but I was wondering what watch you're wearing? I think it looks great

Gram Schmidt is good for paper and pencil calculations but i heard that it is numerically unstable and I should avoid it when I write program for QR decomposition Householder reflections or Givens rotations are better choice for those who want to write a program Silly , or maybe not in Householder reflections we need transpose of matrix to get Q and square matrices are easy to transpose in place Transpose of rectangular matrix also can be done in place but it is not so easy

I thought u2 hat was perpendicular to V1, but apparently that's what v2 is? Or is u2 hat supposed to be parallel to V1?

Your enthousiasm is amazing, the only thing that triggers me is that you put your line of your Q on the wrong side !

Good video! I looked very good. What do you think of Jimmy Hendrix? If you like my guitar and harmonica you will be happy.

The watch steals the show

3:16 what does he mean here? what is rescaling a vector ? just getting rid of the denominator ?

Dr Peyam.. can you please explain what LU decomposition is.. I kind of noticed in my textbook... but no idea what it is..

in W1 , where did you get 1/3 ? and what is W1? you said its the lenght of vector[2 2 1] it should be 3 . but why its 1/3?? i dont get it

Thankyou for being successful in successfully wasting my time

pleaseee in 03MIN.12 why the first resultat is 15/9 !!!

Dr Ariya from Krish

Do 100 integral challenge!!!

What, if you define a kind of Matrix-Product with the compositon of the elements: A = { {a11(x), a12(x)},{a12(x), a22(x)} } and B = { {b11(x), b12(x)},{b12(x), b22(x)} } So that, A°B = { { a11(b11(x)) + a21(b12(x)), a12(b11(x)) + a22(b12(x)) }, { a11(b21(x)) + a21(b22(x)), a11(b21(x)) + a21(b22(x)) } } Linear Algebra is boring, because I never understood it well. Make more videos about this crazy fractional calculus stuff! Something like this: (d/dx)^f(x) x = f'(x), where f(x) is the order of the derivative. Or functions that transform other functios to their derivatives: g1(f(x)) = f'(x), g2(f(x))= f"(x), ... where gn depends of (d/dx)^n f. Then you could "maybe" generalize derivatives by these functions --> g0.3(f) = (d/dx)^0.3 f

IR=V fin.

6:50 known Q find R

First uwu!

08: 10

Orthogonal Matrices are a bit strange anyway. I will never understand why you call a Matrix with orthoNORMAL column-vectors orthoGONAL and not orthonormal. Most of the time I love maths, but sometimes I hate it xD.

Your V's look exactly like your U's

t amo gringo, entendi como el putas no mk lo amo me ayudaste a estudiar para el parcial no nea feliz

Do you put the slash in the wrong place in "Q" just annoy viewers like me!?

「動画の音が良くない」、

The math people call this Q is semi-orthogonal matrix. They define that orthogonal matrix must be square. en.wikipedia.org/wiki/Semi-orthogonal_matrix