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you are awesome man, I havent had the time to check all your videos but I will soon, thank you very much for doing these

Thank you so much i could do the exams well but never really fully understand why, simply memorised all the formula and cases, it was such a pain...until your lecture. it feels that I had been sick but finally got cured. Thanx

Thanks so much for these wonderful, clear video!

This is so beautiful. Thank you!

You do great videos keep it up!

fantastic video, thank you very much!

How did you get the eigen vectors if someone can explain, I got the first eigen vector by gaussian elimination, however struggling to get 2nd and 3rd eigen vector for 4 and 3.

Thank you. The explanation is very clear. The sound and tone are very good. I like the fact that you started with numbers and specific example. Thank you.

Great video!

great explanation! Thanks alot!

Solution of the question is clear... Gr8 lect

Very nice video, thanks teacher kane.

Thank you!

2:20 I didnt understand how you got the third eigenvalue. I'm kind of new at this. Can somebody please explain?

fantastic

Great Lecture. His explanation is very straightforward.

That was beautiful Saved it in my playlist

Starting at 4:53 when converting the 3 separate vector equations into a single matrix equation, how do you know in which order the eigenvalues (7, 4, 3) lie diagonally in Lambda matrix shown at 5:21? If you skipped some steps, could you please explain the work?

how did you find the eigen values?im confused

Thank you! :) Suscribed!

Well Done

Simply beautiful.

amazing , wonderful! thank u very much ,

thanks good vid

Thank You !

thank you grazie merci شكرا gracias

I struggled to actually understand what decomposition was all about (let alone eigenvalue decomposition). Thanks so much for making it cristal clear! You sir are definitely the best!

Bravo

No doubt I would not have this question if I had followed your entire course, but can you tell me why it is immediately obvious to you that 4 must be an eigenvalue simply by virtue of the fact that (1) it is the only nonzero value in column 3 and (2) it is on the diagonal? What is the reasoning behind that? I wish I knew more shortcuts like that for finding eigenvalues!!

thank you professor

around the 5 min. mark:: this should get (v_3)(l_3) =[-3 3 15] but the last column for "A times 3rd eigenvector" should be (A)(v_3)=[-3 3 25] so they are not equivalent. Whats happening? did i mess up?

This is the 10x slow motion version of my prof lecture.

Well explained.

Thanks ,it helps me understanding the deep learning by Goodfollow

Where is the video which shows how you computed the eigenvalues and eigenvectors

a similarity transformation, of the matrix LAMBDA.... haha, I enjoyed that edit. Thanks so much for this informative video!

it's better to explain why the eigen-vector matrix times the eigen-value matrix is equivalent to the eigen values on a right-matrix(eigen-value matrix) time the columns on a left-matrix(eigen-vectro matrix) because intuitively that's not how the matrix multiplication works. In fact, it looks that way because the right-matrix is a diagonal matrix.

Namaskaram Kane

ABC kids

Not understand anything