As a math major, I scored a perfect 100 on my Linear Algebra exam in 1974. However, just two days later, I couldn't recall a single thing.
A few years ago, with ample free time, I decided to refresh my (nonexistent) memory by watching online linear algebra lectures from various professors. I was surprised by their poor quality. They lacked motivation and intuition. Khan Academy offered no improvement. Then, someone recommended Linear Algebra Done Right (LADR). I read it three times, and by the third iteration, I finally began to appreciate the beauty of the theory. Linear algebra is a purely algebraic theory; visual aids are of limited help. In short, if you have the time, I recommend reading LADR. Otherwise, don't bother.
he was a physics and math major and did not know eigenvectors and eigenvalues? i would like to know how is this possible. can someone explain it to me?
> The most notable of these are the synthetic division method for polynomials, the various trigonometric identities, and differentiation of products and quotients of functions.
So he learned nothing you already know at 15. Or younger in Asia.
I think he forgot his goals because it doesn’t even mention eigenvectors.
I am surprised because it is not a difficult thing to understand? It is a vector that when multiplied to a matrix (which in almost all cases would change the direction of the vector), in fact only scales it - and does not change its direction.
The scale factor is its eigenvalue.
So if you hav [[2,0],[0,3]] this should when multiplied to a vector give you [2x,3y]. But if you supply the vector [1,0] or [0,1] you see that the result multiplies that vector by two. So any multiple of these eigenvectors (e.g. [10,0]) will result in a doubling of the vector.
Jason Roberts, the founder (and primary coder) of Math Academy, has been podcasting for over 15 years and has been talking about Math Academy and its inspiration, origins, business fundamentals, financial realities, and ambitions on the podcast for many years. A lot of that discussion is distilled in the Math Academy about page (https://www.mathacademy.us/about). If you want to check out the podcast, it's here: https://techzinglive.com/
Jason also coined the term "Luck Surface Area" which has since been popularized by a number of others.
I haven't used Math Academy myself (although it's something I intend to try one of these days), but I can safely vouch that Math Academy isn't a fly-by-night shallow edtech grift. They've spent a small fortune and thousands of hours developing and refining content and curriculum. Math Academy is a thoughtful, intentional, well-manicured solution.
To be honest, I just read the introductory post, and it'stated there that the author wants to do MVC after finishing LinAlg, which is stated as their goal for end of 2025.
As someone that has the same end goal (but probably 2026 for me) - isn't it maybe wiser to do MVC before LinAlg?
Read the whole thing now, slightly disappointed OP doesn't try to tell us what an eigenvector is, based on his current progress.
resource0x ·11 hours ago
A few years ago, with ample free time, I decided to refresh my (nonexistent) memory by watching online linear algebra lectures from various professors. I was surprised by their poor quality. They lacked motivation and intuition. Khan Academy offered no improvement. Then, someone recommended Linear Algebra Done Right (LADR). I read it three times, and by the third iteration, I finally began to appreciate the beauty of the theory. Linear algebra is a purely algebraic theory; visual aids are of limited help. In short, if you have the time, I recommend reading LADR. Otherwise, don't bother.
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i2go ·15 hours ago
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pinoy420 ·7 hours ago
> The most notable of these are the synthetic division method for polynomials, the various trigonometric identities, and differentiation of products and quotients of functions.
So he learned nothing you already know at 15. Or younger in Asia.
I think he forgot his goals because it doesn’t even mention eigenvectors.
I am surprised because it is not a difficult thing to understand? It is a vector that when multiplied to a matrix (which in almost all cases would change the direction of the vector), in fact only scales it - and does not change its direction.
The scale factor is its eigenvalue.
So if you hav [[2,0],[0,3]] this should when multiplied to a vector give you [2x,3y]. But if you supply the vector [1,0] or [0,1] you see that the result multiplies that vector by two. So any multiple of these eigenvectors (e.g. [10,0]) will result in a doubling of the vector.
This is not a difficult concept. By any means.
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trentnix ·9 hours ago
Jason also coined the term "Luck Surface Area" which has since been popularized by a number of others.
I haven't used Math Academy myself (although it's something I intend to try one of these days), but I can safely vouch that Math Academy isn't a fly-by-night shallow edtech grift. They've spent a small fortune and thousands of hours developing and refining content and curriculum. Math Academy is a thoughtful, intentional, well-manicured solution.
barrenko ·7 hours ago
As someone that has the same end goal (but probably 2026 for me) - isn't it maybe wiser to do MVC before LinAlg?
Read the whole thing now, slightly disappointed OP doesn't try to tell us what an eigenvector is, based on his current progress.
Show replies