Perform Linear Regression Using Matrices

[@smoothxtc]

Finally - someone who can "teach" the concepts vs. just reading slides and equations - You Rule!

[@Heloisa57661]

This video is really great. I have seen a lot of youtube videos about linear regression using matrices, but none of them was that clear and pedagogic. Thank you.

[@RichardKronenfeld]

Great explanation. As a tutor at PC< I had a student with this kind of problem and didnt know how to help him. Now I do.

[@freddieahiabor]

One of the best explanation of linear regression in matrix form

[@stewartwilson1264]

I looked at this in several books, but this helped the most!

[@lilyli_]

most helpful video i've seen in a while! very in-depth calculation-wise and was good review for my exam!

[@leonardo137]

Oh, there is a little mistake. In the slide of 5:27 you corrected the value "25367". I'm sorry for the inconvenience. Thank you.

[@rohankhubchandani3694]

you explained this so much more clearly omg

[@Jpound87]

Man I was struggling until you came along. Thank you so much!

[@Sanyat100]

went through tons of material including course era and udacity but ur tutorial is the best!!

[@jrdetka]

A wonderful overview. Very clear explanation and great pacing. Thank you.

[@camilafarias9666]

Thank you! This is was SO informative. Best content on this subject I've seen so far!

[@karr4291]

Thanks a lot! This deserves my immediate subscription! Hope you make a playlist that contains all kind of estimator methods!

[@Daniel_Johansson]

Thank you very much. A video on the derivation of OLS using matrix notation would be very much appreciated!

[@luxeuto]

I wish I could give this video 1000 thumbs

[@Mathispower4u]

Thank you!

[@shehzadali7074]

I agree!

[@nathankim5387]

Same

[@deadmanthedevilkingofchaos32]

This has helped me a lot.Hope this comes in my end semester exam.

[@ikechukwuenyinnayaazuamair8215]

The best I have seen on this teaching for now. Thank you so much. How wish you can illustrate on another video 'how do we believe E(ei) = 0 '? Assumptions, with example like did here. Best,

[@randydollente9651]

6:24 Looking for confirmation; should the formula for e_i have y_i instead of y_1?

[@FaizahPossible]

thank you, this has been of great help in my assignment

[@brandyhorne1997]

This was really good. I was surprised - Please post more

[@COSMOPOLITANWORLD]

New subscriber! I really enjoyed this video! thanks for this great explanation!!!!

[@andrewntumi131]

You actually rescued me...Many thanks... Love the quote too

[@inquisitiverakib5844]

what a great video ! but plz suggest from where I can have the understanding of the eq at 2:20 thanks in advance

[@ajsctech8249]

Thanks.This is the best explanation of linear algebra i have ever seem. Do you have a statisitcs or data science playlist?

[@Mathispower4u]

Wow, thank you for such a complimentary comment! I appreciate it.

[@Bluebomberman]

Thanks you so much for all your videos you really help us with all your jobs, thanks again

[@BijuBjs]

This is so helpful to understand regression analysis. Thank you so much.

[@ChiranjibPatra]

At time t=2:28 where did the expression of A come in?

[@namgaydorji7224]

Highly efficient and effective. Thank you!

[@hoangalex6880]

So great ! i need more example for ridge regression ! thank you

[@hyrihenry7183]

Watching on 2018. Very helpful sir👍🏻👍🏻

[@cwongtech]

Thanks so much! Explained very well and helpful!

[@jona7600]

Thanks man you saved my day!

[@johncharles3907]

Very nice video, thanks. Just one question, so if beta_hat = [ b m ] with one explanatory variables, does it become beta_hat = [ b m1 m2 m3 ] with three explanatory variables?

[@dipayansarkar3594]

Nice thank you. I have an off-the-track question - Can you please let me know how you have recorded this video? What tool did you use?

[@luizfelipels7]

What if I want to solve with a constraint, like b = 0? (i.e., my regression has to pass through the origin)

[@lindokuhlebrianjikijela4356]

how did you get 25 365?

[@fmetaller]

Great explanation, I wish you could share the slides

[@machinelearningid3931]

Wow, this is awesome man, thanks

[@ranigeorgemouniraziz7294]

Really well explained, thank you :)

[@ahmed.bhewary775]

where I can find the playlist

[@AlpinAdha]

thank you, you help me for my exam

[@iyadjabr]

Thanks! This rescued me

[@erickemayot9552]

Thanks for the use cases

[@rafaelzanfolin7745]

Hello Sir, watching in 2018. First, thank you for the explanation, and second: what software are you using in this video? Thank you & have a nice day

[@Semnyawenda]

Wow, super useful, thanks a million!

[@serg8004]

great video, thank you!

[@ambujsingh6214]

Awesome video! Well explained every point. Thanks for uploading this video :-) Could you please upload for Logistic regression too. Please :-)

[@the2abraxis]

Great video!

[@oligillin5526]

you're a hero

[@livetolearn477]

Thanks. Awesome video.

[@jankovskialeksandar]

Thank you so very much for the video.

[@harrisandrews8741]

Solving the system X^T X A = X^T Y for A by other methods (gaussian elimination, matrix decomposition, conjugate gradient method etcetera), is faster and more numerically stable than computing the inverse of X^T X, especially for large matrices.

[@samikolasa]

Thanks a million 👍

[@amirahope86]

very helpful thank you very much

[@jimturner4937]

This is great! Some presenters have a bland droning voice. Not this guy!

[@elenapanaite6138]

211 how is found?

[@existentialrap521]

thx G u a real one.

[@aloismakau8703]

Helpful.Thanks

[@wenitube]

thank you bro really good :)

[@nicolaiiversen9348]

Thank you so much!

[@markt9206]

cheers mate big help

[@mdafradhossain6243]

super helpful

[@TheNailRouge]

really good :)

[@Mathispower4u]

Thank you for the comment.

[@ZongqiAn]

Who can tell me how to get SSE=E'E in matrices?

[@pumpknable]

THANK U. THANK U. THANK U.

[@soudados9840]

I was interested in the explanation of the formulas. The video was worthless for me.

[@senaitmetaferia9052]

tnks very much

[@melakub.fitawok4498]

is so much intersting

[@felixpersson4593]

dank u senpai

[@RashadibnJafar]

fantastic. if u were here i would hug and kiss you. . thanks so much dude!

[@leonardo137]

I found 25.367 and not 25.365 =(