Preimage and kernel example | Matrix transformations | Linear Algebra | Khan Academy

  Рет қаралды 232,559

Khan Academy

Khan Academy

Күн бұрын

Example involving the preimage of a set under a transformation. Definition of kernel of a transformation.
Watch the next lesson: www.khanacadem...
Missed the previous lesson?
www.khanacadem...
Linear Algebra on Khan Academy: Have you ever wondered what the difference is between speed and velocity? Ever try to visualize in four dimensions or six or seven? Linear algebra describes things in two dimensions, but many of the concepts can be extended into three, four or more. Linear algebra implies two dimensional reasoning, however, the concepts covered in linear algebra provide the basis for multi-dimensional representations of mathematical reasoning. Matrices, vectors, vector spaces, transformations, eigenvectors/values all help us to visualize and understand multi dimensional concepts. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra.
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to KhanAcademy’s Linear Algebra channel:: / channel
Subscribe to KhanAcademy: www.youtube.co...

Пікірлер: 26
@Powd3r81
@Powd3r81 12 жыл бұрын
I can't tell if this video is a good one or not. Linear Algebra just became so freaking hard and none of the math makes any sense. All these vector spaces and sub spaces are so abstract ughhhhh
@spag5296
@spag5296 4 жыл бұрын
7 years later, I'm feeling the same way! although the video was explained much better than my lecturer.
@aminem4626
@aminem4626 4 жыл бұрын
I feel you haha
@razberrycreme
@razberrycreme 12 жыл бұрын
How are you such an amazing teacher, seriously. It would also be really helpful if you numbered your videos so that we know what order to watch it in. but seriously these are amazing. thank you!!!!!
@thomasvitale5250
@thomasvitale5250 9 жыл бұрын
At 0:13 when he coins the term "multiplation" :) Muchas gracias Khan Academy brothas! Your videos are helping me through grad school! Who needs professors on tenure anyways :)
@Bomberofdoom
@Bomberofdoom 14 жыл бұрын
SO THAT IS THE NULL SPACE!!!!! :-O Why couldn't they explain this at the same time they explained us about the null space?!?!?! Now that I VISUALLY see it, I can really understand what we're talking about! Thanks Sal!!
@Sheeeeshack
@Sheeeeshack 6 ай бұрын
Little hair splitting: Kernel is a kind of transformation. It’s not all the vectors. That is basically the difference with NULL.
@grandorottcod1
@grandorottcod1 10 жыл бұрын
kernel== nullspace
@linkwigger
@linkwigger 14 жыл бұрын
Great explanation of the nullspace of T.
@debendragurung3033
@debendragurung3033 7 жыл бұрын
13:16 bookmark, a set of vectors in one domain gets mapped to just a single set in range. Yet still a linear trasforation..... neat
@Waranle
@Waranle 15 жыл бұрын
Thank you Sal
@farmerdave4000
@farmerdave4000 8 жыл бұрын
Thanks for the explanations!
@Zmunk19
@Zmunk19 4 жыл бұрын
does this have anything to do with the kernel trick in support vector machines? (machine learning)
@ad2181
@ad2181 15 жыл бұрын
thank you
@xybersurfer
@xybersurfer 14 жыл бұрын
good explanation
@abhishekagrahari1007
@abhishekagrahari1007 12 жыл бұрын
great explanation
@gubby740
@gubby740 5 жыл бұрын
thx
@s0m0c
@s0m0c 12 жыл бұрын
Gracias!
@mappingtheshit
@mappingtheshit 13 жыл бұрын
Well, I study physics, and for me it is more natural that kernel is the mapping into the identity elements... Or is it just in pure mathematics kernel is mapping to any desired elements?
@DJDKCR
@DJDKCR 7 жыл бұрын
I like to skip ahead and watch these advanced videos so that I can see what I will be able to understand someday.
@haythemoldaccount7953
@haythemoldaccount7953 3 жыл бұрын
I am doing this freshman year help
@rainerrustenberg3824
@rainerrustenberg3824 10 жыл бұрын
I just wonder, that if you will combain the equations at time 7:45 it wil be a contradiction. Why, because: x1 = -3t and, ( x1 - 1 = 3t, gives x1 = 3t + 1), so ( x1 = -3t AND x1 = 3t = 1), but that is when solving 2 linear equations with 2 unknown, sorry, I'am bad. But it sure is a great video, very well. Rainer
@floyd617
@floyd617 13 жыл бұрын
i thought it would be shifted one up, how is it to the right?
@spaceteapot
@spaceteapot 12 жыл бұрын
does he mean the space spanned by the vectors S? because S itself is not a subspace.
@mappingtheshit
@mappingtheshit 13 жыл бұрын
@mappingtheshit or am I just confusing the simple matrices with groups?
@devilpizza123
@devilpizza123 13 жыл бұрын
lol multiplation :D
Bend The Impossible Bar Win $1,000
00:57
Stokes Twins
Рет қаралды 41 МЛН
Oh No! My Doll Fell In The Dirt🤧💩
00:17
ToolTastic
Рет қаралды 13 МЛН
Gli occhiali da sole non mi hanno coperto! 😎
00:13
Senza Limiti
Рет қаралды 24 МЛН
Nurse's Mission: Bringing Joy to Young Lives #shorts
00:17
Fabiosa Stories
Рет қаралды 15 МЛН
Linear Algebra - Lecture 17 - Matrix Transformations
11:32
James Hamblin
Рет қаралды 170 М.
Calculating dimension and basis of range and kernel
13:32
The Bright Side of Mathematics
Рет қаралды 39 М.
Заменил Своего Кота Роботом за 3000$
21:27
TheBrianMaps
Рет қаралды 1,6 МЛН
The Column Space of a Matrix
12:44
MIT OpenCourseWare
Рет қаралды 131 М.
Bend The Impossible Bar Win $1,000
00:57
Stokes Twins
Рет қаралды 41 МЛН