I took Linear Algebra in my 2nd year Electrical Engineering undergrad 34 years ago. Now I am watching your videos and doing problems with ease. Too bad RU-vid wasn't around in 1987. Thank you Dr. Bazette.
Industrial and systems engineering in 1986. Feel exactly as you. Learning/relearning this material is so much easier now. So many great resources at your fingertips. Back then we had essentially one instructor and one or two books.
I used the videos from this channel to fully understand concepts from my calc 3 class and I passed my calc 3 class with a 100%. And now I am using this for linear algebra. Dr. Trefor, thank you so much for explaining things in a visual and simple way for us to understand.
The best part about your teaching is the fact that we can think this intuitively and also visualize the application of linear algebra. I had matrix operations in my high school but never really understood the motive behind studying it. Its through you that I have come to understand the importance of the same.
Hi, I just wanted to say your Linear Algebra videos are a fantastic resource to learn, especially while we are all remote. Your visuals help me understand the Vector space topics so much better. Thanks
As a 3rd year math student, who studied systematically most of the topics that you covered in your videos, I can say that i still learnt so many new things, but mostly filled "lack of intuition" gaps in my knowledge. I am glad someone like you exists on RU-vid. If I knew for this channel 3 years before, I would have gone through much less pain. Greetings from University of Belgrade! P. S. I think you should change your microphone position, you sound kind of shallow. Maybe it's just me.
Could you do a video about Clifford Algebra (Geometric Algebra) ? There are a few math videos out there explaining the algebra, but I'd love to know how to appy it to real life (engineering) problems. I love all your other courses btw. I was never good at math. I had terrible teachers, I didn't give as much effort as I should, and never managed to get all the rules into my head (well not for the "long term" at least... maily because of a lack of practice) But now watching all your calculus and LA classes and trying to apply your learning strategy and I really feel like I am getting more confident in my problem solving. I set up an anki deck to engrave the rules into my brain once and for all. I am really aiming for a more thourough understanding now. Your videos help a lot. Thank you!
Thanks. Very very good. Minor point: at ~11:21, the last term in the polynomial t1x1 + ... + t_n x x^n should probably be t_n-1 x x^n. I didn't see this minor typo mentioned. Thank you again for excellent videos.
1000th like woo. By the way I am just curious, is there a case where the polynomials are linearly independent but don't span full P2? other than the obvious case that we don't have a polynomial representing x^2 or x or x^0.
If we take u1=x and u2=-x then u1 + u2= 0 , it is zero polynomial. And degree of zero polynomial is not defined, so, 0 will not be in this space. So how this space becomes vector space?! Please correct me if I am wrong..
There is also scalar's inside the factorization. I seem to be seeing it everywhere now that I know where to look. The scalars are the zeros only. It doesn't scale the regular function. (x-sqrt(2)*r1_He[5])(x-sqrt(2)*r2_He[5])(x-sqrt(2)*r3_He[3])(x-sqrt(2)*r4_He[3])(x-sqrt(2)*r5_He[3])
Should "Span {v1,...,v2}" denoted as "Span {v1,...,vn}"? And that "Span {v1,...,v2} = V" denoted as "Span {v1,...,vn} belongs to (not equal) vector space V" ?
Hello!!! I think , and i say i THINK (i could be wrong), around the minute 11' , wouldn't it be the formula t1.1 + t2.x + ... + tn.x^n-1 ? Or am i making and error. I love your videos by the way ♥ ♥
Math of machine learning is just calculus, linear algebra and statistics 😀 you may also benefit from learning how to do these topics with a programming language.
