Kernel and Image of a Linear Transformation Example 1 | Linear Algebra | Griti

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Опубликовано:

19 сен 2016

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Комментарии : 60

@lol_perry6835 4 года назад

the intro song XD

@creatorchris712 4 года назад

The outro song :)

@qlowquest 4 месяца назад

XDXD

@magdalenapsenickova620 4 года назад

this was literally the most helpful video I have ever watched tbh dude made my entire semester's topics fall into place in six minutes five seconds but ok...

@notevennelson Год назад

The intro track got me, brother. I thought my RU-vid Music was playing in the background, quickly clicked pause, only to realize it was an intro track, lol

@vanessanoel4197 5 лет назад

That's legit one of the best lin alg videos I've found! Thank you!!

@fryderyksitnik7884 2 года назад

This channel is way too underrated. So much great content without reward.

@urtvplugg5603 6 лет назад

Wow. clear and simple explanation. thanks

@vanessamerino1665 Год назад

Amazing video, I understood everything, thank you :)

@alemanicorda 5 лет назад

Very clear, thanks

@lancelofjohn6995 2 года назад

Very helpful video, understanding the kernel and image of matrix is not difficult.

@guillem_dlc 6 лет назад

You could also stretch and shrink the vectors. A matter of elegance.

@jerrerock 5 лет назад

oh wow, I always thought every matrix had just 1 span given, now I see it is just a way where you can show some transformation of the matrix more simpler.

@durgaprasada226 3 года назад

Bro can u make video or point to source where and how linear algebra is used in aerospace engineering

@joelkoodarkking 2 года назад

bro. i didnt know how to do this in class for 1 month (in a summer class). I learned it in 10 minutes because of you! THANKS!

@augustusprime0_o Год назад

So helpful. Thanks!!

@hardiksharma7100 3 года назад

loved it keep it up:)

@jianansheng5120 Год назад

Thank you!

@masterojofficial8967 2 года назад

it was so good

@MustaphaAjara 24 дня назад

Sorry I thought for row echelon form the pivot don’t necessarily has to be me 1 or we are suppose to reduce to reduced row echelon form urgent answer pls anyone 😊

@mengis2012 7 лет назад

simple and clear explanation. Very helpful thanks!

@griti515 7 лет назад

You're welcome, Gerry. We'd appreciate a share. We have more than 3000 videos to help with math, physics and chemistry.

@khanhduy3364 2 года назад

thank you

@chrisgreening9313 6 лет назад

sicc dude thx

@devendrayadav6393 4 года назад

please verify rank nullity theorem

@michaeljeynes6495 2 года назад

you need to explain at start why you choose such a special matrix with the rows being in ratio 2:3

@michaeljeynes6495 2 года назад

also it seems the kernel and image things are perpendicular

@metebas3400 5 лет назад

You deadass saved my life B

@ireleuduokhai9174 Год назад

lmao is that roc marciano at the start of a lin algebra video

@iTbagg5 5 лет назад

Is there a reason why you divided R1 by two first?

@iTbagg5 5 лет назад

wait I know why now lol silly Q

@the_maskedtv2196 Год назад

The opening track

@user-gy4ds8vv1n 6 месяцев назад

thanh you ma friend

@Loots1 3 месяца назад

damn never heard a dope hip hop track as an intro to a math vid

@jacobloose5088 3 года назад

Not enough credit to outro song hahaha good work

@suniltrivedi1291 6 лет назад

You made a slight mistake in second step of row reduction of the matrix . Its R2- 3R1

@justinweaver375 3 года назад

5:57 "Fuck outta here"

@huzzman6324 2 года назад

great video, your dimensions are off though! The basis of the kernel and the image alike is two I think. Currently, you have it listed as the dim(ker)=1, which, using rank nullity, the dim(Im) = 4-1 = 3, despite having the same amount of elements (2) and restrictions (0) as the kernel.