A Vision of Linear Algebra Instructor: Gilbert Strang View the complete course: ocw.mit.edu/2020-vision TH-cam Playlist: th-cam.com/play/PLUl4u3cNGP61iQEFiWLE21EJCxwmWvvek.html In this video, Professor Strang provides an overall look at linear algebra by highlighting five different ways that a matrix gets factored. For every matrix A, four key vector spaces are the row space and nullspace of A and its transpose. To compute with A, we factor it into A = (column space basis) times (row space basis). The simplest basis uses independent columns taken directly from the matrix A. The best bases of all use *orthogonal* vectors from the column space and the row space of A. These “singular vectors” produce the great Singular Value Decomposition! License: Creative Commons BY-NC-SA More information at ocw.mit.edu/terms More courses at ocw.mit.edu We encourage constructive comments and discussion on OCW’s TH-cam and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at ocw.mit.edu/comments.
Thank you so much for all you've done for the field of applied mathematics and your exceptional teaching. You've shown us how to do and think about linear algebra the right way.
Title says it all, he covers five ways to factorise a matrix. If you're new to LA - especially if you don't know what a vector or a matrix is - then this is definitely not the place to start. Even if not, honestly, this is better for someone that has already studied everything covered here but could benefit from it all being put together conceptually. There's a long list of prerequisites to following this; what a basis is, what a linear combination is, how to multiply - nullity / linear dependence / identity / space / span / rank... You don't need to be a genius to get this, it boils down to geometric simplicity which (in lower dimensions at least) you can picture in your head but it's not a beginner's lecture.
surprised by your own slides, no visuals save text, you've been doing this for how many decades and this is the panicle of your ability to communicate, explains why most universities fail most of those who enter. ... Bill Nye you are not.
A Vision of Linear Algebra
Instructor: Gilbert Strang
View the complete course: ocw.mit.edu/2020-vision
TH-cam Playlist: th-cam.com/play/PLUl4u3cNGP61iQEFiWLE21EJCxwmWvvek.html
In this video, Professor Strang provides an overall look at linear algebra by highlighting five different ways that a matrix gets factored.
For every matrix A, four key vector spaces are the row space and nullspace of A and its transpose.
To compute with A, we factor it into A = (column space basis) times (row space basis).
The simplest basis uses independent columns taken directly from the matrix A.
The best bases of all use *orthogonal* vectors from the column space and the row space of A.
These “singular vectors” produce the great Singular Value Decomposition!
License: Creative Commons BY-NC-SA
More information at ocw.mit.edu/terms
More courses at ocw.mit.edu
We encourage constructive comments and discussion on OCW’s TH-cam and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at ocw.mit.edu/comments.
Thank you Prof. Strang for all you have done and taught us.
Gilbert Strang 🙌. I have learned a lot from you. Happy retirement.
Strang is the best professor I never had
My most inspired person alive, Dr. Gilbert Strang
Glad to see a new video by Professor Gilbert!
Thank you so much for all you've done for the field of applied mathematics and your exceptional teaching. You've shown us how to do and think about linear algebra the right way.
Such a great news to find new material from Prof. Strang. A living legend.
The king of linear algebra is back
YES! MORE GILBERT STRANG!! Sir, I thought to never see new videos from you.
Your great book on calculus helped me a lot to pass my one last math subject 🎉❤ now I'm graduating
I love you, Gilbert! 💌💌 I loved your lectures back in 2007 in graduate school (back then) and I love them now.
master of the linear algebra
Thank you Prof. Strang for sharing us the great insights to the beauty of the linear algebra.
Thank you very much, Professor Strang! Brazilian students thank you for your contribution!
I am happy to see you explaining so smoothly...❤
Thank you, Prof. Strang!
Never was and probably never will be an MIT student but the comment section is so wholesome! Have a great retirement prof. Strang.
Never heard of him. He doesnt seem that wonderful to me so far, tbh.
@@deltalima6703he's Richard feynman of linear algebra
Professor Strang, thanks a lot.
Thank you Prof. Strang ❤
Thanks so very much, Professor Strang!
A little sad when you said “final edition”, it’s too late to meat you,great professor!
Thank you, Dr. Gilbert Strang!
Great Gilbert! Always admire you!
thats how legend talk and teach.
Phenominal lecturer.
Thank you, Dr. Strang!!!
This notification made me smile :)
Yay, Gil is back! ❤
Love these lectures/videos. Thank(s) for the knowledge…
Strang turned linear algebra into an addictive drug.
Hats off to you sir Gilbert
Thank you Dr. Gilbert Strang
Thnak you, Prof. Strang,
GRAZIE , Prof.Strang !!
GILBERT STRANG IS A LEGEND ❤
真·神。感谢上传。
Our true Neo in this version of Matrix
I can only hope to have this man's mental capacity at his age.
Thanks Prof. Strang.❤❤❤🙏🙏
Thank you Prof
Trigonometric-function-subspace(precise-hyperbolic-tangents,cosines,sin)….
thank you
Thank you🙏
This is so cool
No, thank you Dr. Strang.
This is a blessing
Nice job! 🤠
un grande enseñando
Let my man rest for a while MIT
Just a question: Are these college lectures because here in India it's something we have to study in school?
Who is teaching you matrix decomposition in school? What board are you talking about?
48:03 accidental British moment
Matrixazo
"Latest and final edition..." 🥺🥺
OK!
1st One To see The Video🎉
I am so envious!
All white, all men, all over 50.
🙏♾🎁
🎉🎊👏🏻👏🏻👏🏻
what the hell is he talking about
Title says it all, he covers five ways to factorise a matrix. If you're new to LA - especially if you don't know what a vector or a matrix is - then this is definitely not the place to start. Even if not, honestly, this is better for someone that has already studied everything covered here but could benefit from it all being put together conceptually.
There's a long list of prerequisites to following this; what a basis is, what a linear combination is, how to multiply - nullity / linear dependence / identity / space / span / rank...
You don't need to be a genius to get this, it boils down to geometric simplicity which (in lower dimensions at least) you can picture in your head but it's not a beginner's lecture.
surprised by your own slides, no visuals save text, you've been doing this for how many decades and this is the panicle of your ability to communicate, explains why most universities fail most of those who enter. ... Bill Nye you are not.