Відео

babe wake up drew werbowski uploaded again

Good video,but can I ask something. Since the definition of a bases states that not only must the list be linearly independent but must also span the entire vector space. How do we prove that or is it not necessary for this proof?

Hi Drew! I'm Victor. Good video that I totally understood

😂😂😂🥶🥶🥶🥶🥶😮😮😮😮😮🤯🤯🤯

babe wake up drew werbowski just uploaded

Why do you use j instead of i for the imaginary unit?

You are such an amazing teacher!

bro! You are my hero,It's a pity that I discovered this channel too late, I have an exam this afternoon.

thank you so much.....

So why nulity is 1?

i have a question here basis of kernal is empty then.it has no dimension..means zero dimension.but dimension.of Kernal equals nulity so here we seee nulity is 1

Thanks bro you actually saved me

fantastic job

3 years later and Drew, sir you are amazing. Thank you so much, you are a life saver!!!

Why is it -x(-sin(x)) at 4:01, not -xsin(x)?

Nice, succinct explanation. I just wanted to confirm what an Eigenspace is and this was the perfect video. Didn't need to wade through a 20 minute exposition on all things "Eigen" to get there. Cheers!

Good

Nice. A tip for the future, start off with the most central, interesting and motivating information, namely drawing the shortest distance from point P( 3,3,1), and from the start telling that the closest distance must be a line perpendicular to line L. THEN you construct the vector equations that gives you that sought vector ( the perpendicular one ) and the distance along it from 3,3,1 to the line.

There are unknown way to visualize subspace, or vector spaces. You can stretching the width of the x axis, for example, in the right line of a 3d stereo image, and also get depth, as shown below. L R |____| |______| TIP: To get the 3d depth, close one eye and focus on either left or right line, and then open it. This because the z axis uses x to get depth. Which means that you can get double depth to the image.... 4d depth??? :O p.s You're good teacher!

thank you, it helps me with my classwork. Blessings. : )

Why all of you guys placing vectors in matrix column by column you just do smth strange not RREF I mean you placed x x x y y y z z z Instead of x y z x y z x y z when you RREF second one you substract and adding some vectors to find depended once But actually thing that you did here seems to me wrong because you adding and substracting whole xs or whole ys or whole zs of different vectors WTF math always worked by logic,am i wrong or your solution is wrong,can someone explain

youre so good man!

Thank you

When you want to teach any concept, solve problem for generic values not for specific values.

👍

This video is by far the most thorough and best explanation. I love that Drew does a short review before solving the problem. He makes it so easy to understand the concept.

cramming for an exam right now, ive watched tons of videos and read the entire textbook chapter, nothing helped me understand the topic better than this video. you are a godsend, i know this video is old but thank you so much!

best explanation of topic .... finally i understood the topic ... it is simple but our teacher make it very hard.

you made the most clear drawing of a linear algebra problem I have ever seen, it makes everything so much clearer to be able to understand which line, vector or plane is which, thank you

Bro left us and now we're stuck with mrs frost again- (Also the only other person in the comments ik is Michael- im suprised i havent seen anyone else ik) How many eggs could fit into a microwave 👨‍🦲

Your channel saved my butt for studying for a final.

There are two different topics I was trying to learn today and I was looking all over the internet for videos/clear explainations. Your channel is the only one with good videos in these topics. I really appreciate this. Thanks man I hope you make it big!

11:22 I think there is a mistake, it should be the span of {v1, v2, v3, v3} = span {v1, v2} , not span {v1, v2, v3 } = span v1, v2, since there are four vectors we started with in Col(A).

interesting you say that applying a linear transformation is 'shifting space'. So that is one way to think about it, as a mapping between two spaces , the departure space and the arrival space, or as transformation of the departure space. A linear transformation is equivalent to matrix multiplication, and for the null space we are looking for solutions to A*x = 0 , where x is an n x 1 matrix of "solutions" and A is a given m x n matrix. When x varies you have a map from R^n -> R^m , defined by x -> A * x .

drew im michael from f8f pls respond

my fav content creator drew werbowski

next upload when

Savior

You talk way too much, I just need the example

AWESOME EXPLANATION 🌟

thank you so much for making this video! :) I was wondering if you could possibly explain one-to-one and onto?

what is there is a free variable in the reduced form?

Bro you're a goat I never comment but u made everything so much easier to understand than the other tutors who just yap about definitions, but you explain the intuition. Love it def gonna start watching u more for linear.

Good boy

Tysm

good job nerd, i actually learnt something

THANK YOU!!😀😀😀

Great video! Thanks

Thanks! You do just a great job of explaining this!

explained it better than my prof and my textbook combined. appreciate it man thank you