Inner & outer products | Lecture 5 | Matrix Algebra for Engineers

[@ProfJeffreyChasnov]

Find other Matrix Algebra videos in my playlist kzbin.info/aero/PLkZjai-2Jcxlg-Z1roB0pUwFU-P58tvOx

[@stearin1978]

It would be nice to write here Inertia tensor in the form Sum (x^Tx) I - xx^T. Both 2 products in one basic physical entity. Nice video anyway.

[@MONKEYDUDE2701]

man this is quality teaching here. you my friend can call you a teacher unlike a lot of other "teachers"

[@harsh_rana]

thanks sir I am from India i need to know about inner and outer multiplication during programming you helped me very well once again thank you sir

[@karam3045]

Dont think there is a better teacher than this, thank you.

[@HeroDw-n2m]

Chasnov is a really cool title for a maths teacher.

[@spontaneousbagpacker9447]

This clears a lot of my doubts as I am learning SVM kernels. Thanks Jeff!!

[@danielgray8053]

Thanks Jeffrey I really appreicate this series. I am taking graduate level Machine Learning class and have never taken linear algebra before. I know, stupid. I tired watching 3blue1brown's series which is a short 17 lectures series that is great was very interesting but not perfect for my needs. Than I tried watching the 144 video khan series on linear algebra. I got to video 32 lol. good, but once again not perfect for my needs. Thank god I found you! Perfect for what I need right now. Thanks so much I was feeling pretty helpless until I ran into this.

[@tdpro3607]

3b1b only focus on the irl uses and visualisation, as he states that there are already many resources out there that teach you how to compute things

[@Leila0S]

I'm now in your same situation and did your same steps and thankfully I found this playlist and another channel's linear algebra playlist very satisfactory.

[@alimurad5312]

So helpful. Thank you for making such high quality lectures available to everyone. Much appreciated.

[@theman2449]

High quality lectures that are short, easy to understand, and can be applied to many situations. Thank you very much.

[@dagraves]

You are a great teacher. Totally textbook.

[@kiichitakeuchi]

Your coursera course was fantastic. Thank you!

[@nature_through_my_lens]

Which one?

[@mikejason3822]

Clear, short and to the point. Thanks.

[@LuciaSilva-ek3qr]

In this short video, very clear and helpful. Thanks a lot.

[@eric5258]

How do you film these videos? I assume you're not actually writing backwards. Are you filming yourself from both the back and front and then overlaying the individual videos?

[@ProfJeffreyChasnov]

Video is shot through the glass, and the software mirror reverses the writing.

[@ccuuttww]

I would say this is linear transformation in linear algebra --- The reflection are u using left hand for writing?

[@magmasceptre]

I think he just puts the camera on the other side of the glass pane and he would write on the other side. After which the video will be flipped left to right.

[@Vicky-pb5hg]

You may wish to read about "Lightboard", invented by Prof. Michael Peshkin of Northwestern University.

[@MONKEYDUDE2701]

bruh he just mirrors the whole Video bro.

[@JulieIsMe824]

I bought your “ Matrix Algebra for engineers” on coursera and I found it so helpful!! Thank you so much! Can you do more intermediate/advanced matrix algebra courses?

[@ProfJeffreyChasnov]

Thanks! I am working on a vector calculus course now. Maybe you can find other more advanced linear algebra courses on Coursera or EdX? Or on MIT open courseware?

[@JulieIsMe824]

Jeffrey Chasnov Haha...I’m so excited you replied!!! Thank you so much for the advice!

[@abhisheksahu616]

Thanks, am going to check this one now.

[@subhashbhambhu8792]

Hii

[@29ibrahimsayed95]

Very Beautifully Explained.

[@sajithk9650]

I like your way of presentation. It's as if you are enlightening as from abyss.

[@hitesh_sewani]

You saved me. Thanks for the to the point video.

[@rationalistfaith]

Good stuff and love the format! Thank You!

[@ahmedmuhammed6905]

U just wrapped it up, thanks alot

[@RestartUPSC2026]

Your explanation was awesome Sir!....

[@saschaffer]

Thanks professor- great explanation.

[@nikhilaryal]

Thanks Jeff, you're amazing!!

[@AJ-et3vf]

Great video. Thank you

[@hafidhrendyanto2690]

Thank you for this material, I am currently learning Matrix Factorization algo, its hard to understand it but it turn out Im just missing this fundamental concept about outer product.

[@kelvinmaina1189]

Thanks....very much i have understood the concept and your video is far much clear....if possible i would like to see your videos on solving problems in linear algebra and analytical geometry if you do present thanks

[@allanshu177]

really helpful! respected prof.

[@chillynights4055]

Thanks for clear informative video. Helped a lot

[@xoppa09]

Thanks to the transpose operator, without qualifying further, a 'vector in R^n' is a column vector or nx1 matrix, and a 'row vector in R^n' or 1xn matrix would just be the transpose of the nx1 column vector.

[@parsakei9006]

This is such a great video thank you.

[@akshaankaware1787]

I love how he just walks away at the end casually

[@EllisAlcantara]

You’re great. Thank you!

[@zhuoyuelyu]

It's so clear, thank you so much!

[@Baron-digit]

Well explained, thanks!

[@Rudrazz]

Awesome video

[@jamessterling955]

Did you really learn how to mirror your writing? Excellent video, thank you!

[@ProfJeffreyChasnov]

kzbin.info/www/bejne/jXPCdJShpqqfh5I

[@vanilin113]

It would definitely make sense to add the norm of the inner product = ||u|| ||v|| cos(alpha), where alpha is the angle between two vectors - a simple and clear geometric interpretation.

[@ProfJeffreyChasnov]

This comes early in my vector calculus class.

[@ahmedelmattawaa5029]

Thank you very much this is very insightful and useful, are you by chance going to do algorithms?

[@eldraco252]

jeff bezos is that you?

[@zurzakne-etra7069]

jeff bezoz (mr union buster) could never

[@BrickBreaker21]

Jeff Bezos is Walmart Jeff Chaznov

[@kevindave277]

Thank you so much, good man

[@alpsahin4340]

Thanks Jeffrey!

[@xCarbon02]

what if the transpose of V has multiple rows? How do we compute the outer product?

[@Edioteditor]

Thanks professor

[@JimmyXC234]

Good work.

[@موسىآلجيلاني-د7ع]

Thanks well method

[@davidmurphy563]

I'm trying to find the meaning to the outer product, the calculation is trivial but you tease that the matrix has low dimensionality. This is what i need to know but I can go through an entire engineering course just to know this one thing when I'm not an engineer... Anyway, was an excellent lesson, thank you.

[@ALIRAZA-zv5mn]

what are the original and strong definition of inner product . can u guide me about this topic. sir,

[@ashutoshjha225]

really helpful

[@maartjet6906]

very helpful!

[@shymaaabdelkhaleq7254]

thanks

[@pearechen5111]

super helpful

[@curtpiazza1688]

Excellent teaching! 😂

[@magdynasr6639]

what is said in hours is said in 9 minutes! thanks

[@NovaWarrior77]

thanks!

[@nikhilnarayane680]

thank you for that wonderful explanation..:D

[@梁廷睿-t5k]

Great!!

[@petelok9969]

Jeffery can we apply these rules to square matrices for example? Peter

[@ProfJeffreyChasnov]

This video is about column and row vectors.

[@abboszaitov2093]

Hello from Uzbekistan

[@abhishek_sengupta]

Thanks!!

[@ndngdippchn]

Thank-you

[@ytpah9823]

cf. outer product vs. tensor product?

[@eylmaz6696]

what is the system that you use here to explain the courses

[@mauricioalfaro9406]

Subscribed!

[@tadeletekeba13]

thank you so much

[@princesatartaruga444]

Muito bom 👏👏👏

[@MrSidTaylor]

That's fine for row and column vectors, but what would be the outer product of two 2X2 matrices?

[@ProfJeffreyChasnov]

It's only defined for vectors.

[@MrSidTaylor]

@@ProfJeffreyChasnov Would that be the tensor product?

[@ProfJeffreyChasnov]

@@MrSidTaylor Yes

[@fwsgsdg1977]

thx

[@stefanosmitsios7694]

what is that dot product tho?

[@ccuuttww]

more topics?

[@-error-404]

How can he write it like this

[@JVenom_]

33 slides or 1 screen this is lit

[@anshukalshyan5967]

Besttt

[@alexandradobrescu8795]

Thank you, Jeffrey! Could you please tell us how the outer product can be helpful in ML or, at least, indicate the video where you tackle this subject?

[@matgg8207]

did he actually have a glass in front?

[@pete4043]

wow, Jeff Bezos teaching math

[@TomSkinner]

It's a side gig for some spending cash.

[@nat.serrano]

why uTv becomes a 3,1 and uvT becomes a 3,3,...??

[@RealLifeKyurem]

Nat Serrano vector and matrix multiplication are not commutative. u·v produces a scalar, because u^T is a 3×1 matrix, while v is a 1×3 matrix. (3×1)(1×3) = 1×1. So no, u·v doesn’t produce a 3×1 matrix. u×v produces a matrix, because u is a 1×3 matrix, while v^T is a 3×1 matrix. (1×3)(3×1) = 3×3.

[@austinosogwin4121]

he writes backwards so well lol

[@bravo803]

One Pen Man

[@bastienp7334]

Oh he is actually writing it all in mirror :)

[@bastienp7334]

oooh no i guess the video is mirrored 🤯 if i were to do that i would actually write in mirror because it's more fun hehe

[@ProfJeffreyChasnov]

@@bastienp7334 kzbin.info/www/bejne/jXPCdJShpqqfh5I

[@bastienp7334]

@@ProfJeffreyChasnov Hahaha thanks

[@Brandon-t2c]

great explication, glass board :V

[@GarvitKhera185]

Are you left-handed or right-handed ?

[@ProfJeffreyChasnov]

right

[@OprichnikStyle]

too good to be true

[@-long-]

check this kzbin.info/www/bejne/rXSypqhmYtRoj6s

[@herbertwhite3665]

how tf is this man writing this? he can write backwards??

[@ericklestrange6255]

0 intuition, just formulas yet useful

[@leewilliam3417]

Mmmm😊

[@abinayasivasamy4708]

Hope, am not the only person to suddenly see Jeff Bezos, and then realised.. Good teaching

[@NikolaosLedZeppelin]

how this guy writes that way ????!!!!

[@benafrem]

Did anyone else mishear u2 as KZbin 😂😂

[@cowmata8492]

GG

[@vanshajvidyan8458]

Am I the only one who thinks he that he sounds like Yondu

[@adamsterish]

thank you jeff bezos

[@blueice1364]

I think all the white bald guys are named the same...

[@RualddeBruyn]

Thanks

[@blueice1364]

Thank you so much.

[@bilalabbad7954]

Thanks a lot

[@ASHNAY9]

Thanks🙏

[@ebramsaif3999]

thanks

[@shreyaskumarm3534]

Thank you so much