So far I think I prefer the visualizations in <a href="http://immersivemath.com/ila/index.html" rel="nofollow">http://immersivemath.com/ila/index.html</a><p>For pure visual intuition, I prefer 3blue1brown's Essence of Linear Algebra on Youtube (<a href="https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab" rel="nofollow">https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2x...</a>). Even though they're not interactive, the visualizations themselves are the most compelling and insightful.<p>Has anyone used both interactive texts? My initial impression is that the GA Tech text starts with matrices and applications to systems of equations (like Strang) while the immersive math one seems to start more focused on vectors and geometry with computer graphics applications.<p>Neither seems to have supporting exercises yet which I think really limits their use as primary texts.
This is based on Mathbox which is... brilliant.
Here's the demo blog post that shows off what it can do:
<a href="https://acko.net/blog/mathbox2/" rel="nofollow">https://acko.net/blog/mathbox2/</a>
This looks outstanding.<p>I am a math professor, and I need to choose a book next time I teach linear algebra. It may well be this one.<p>If anyone has in-depth experience with the book, I'd be grateful to hear about it.
I love how approachable the writing style is. It's very easy to write a technical introduction that assumes a lot of pre-existing knowledge of the reader. So far it's a great read for someone like me who got discouraged by notation and cloudy terms before.<p>Looks like it's on pair with the Book of shaders.
Also great resource: <a href="https://aiprobook.com/numerical-linear-algebra-for-programmers" rel="nofollow">https://aiprobook.com/numerical-linear-algebra-for-programme...</a>
Reminds me of the Nicki Case tool:<p><a href="https://ncase.me/matrix/" rel="nofollow">https://ncase.me/matrix/</a>
From <a href="https://textbooks.math.gatech.edu/ila/overview.html" rel="nofollow">https://textbooks.math.gatech.edu/ila/overview.html</a><p>> Most engineering problems, no matter how complicated, can be reduced to linear algebra.<p>Most problems... except a problem of too much linear algebra.
Good stuff.<p>One point of feedback: when making a widget fullscreen and then pressing the back button, you're back at the previous chapter, rather than scrolled at the position you left in the current chapter.<p>I see now there's also a "make small again" button far down in the bottom right, but it's still a trap.<p>Probably it's solved either by having the back button close the widget, or alternatively make the widget look more like an overlay and less like a new page (plus closing with "esc" would also help)
<i>Linear: having to do with lines, planes, etc.</i><p>This definition makes me worry that the book is going to operate entirely in R^n. Is there anything here about substantively different vector spaces?
Wonderful! I remember struggling to make it through linear algebra in college because the teaching style was so unapproachable and disconnected from real applications. It wasn't until I took computer graphics that I really grasped a lot of the concepts.
This is really neat, and it's clear a lot of work went into the polish and interactivity. I'd love to see the elimination examples extended to show how LU factorization falls out of those steps. It seems like a key thing to grasp and lays the groundwork for understanding of related matrix factorizations like symmetric, QR and singular value decomposition.
If anyone is interested in a similar intuitive or geometric guide I open sourced my own notes and you can find them here: <a href="https://github.com/photonlines/Intuitive-Overview-of-Linear-Algebra-Fundamentals" rel="nofollow">https://github.com/photonlines/Intuitive-Overview-of-Linear-...</a>
This is our (my company) take on Linear Algebra, but then with exercises:<p><a href="https://app.bolster.academy/courses/chapters/en/6" rel="nofollow">https://app.bolster.academy/courses/chapters/en/6</a>
This extensively uses the American Institute of Math's knowls[0], which I think is excellent for math documentation.<p>[0] <a href="https://aimath.org/knowlepedia/" rel="nofollow">https://aimath.org/knowlepedia/</a>
Awesome for reference and understanding.
Anyone know of good practice material?
Or maybe thinking of a way of generating practice material that exercises the component skills needed to do/understand Linear Algebra?
I got an A- in linear algebra in college without learning <i>anything</i>, via multiple choice tests and pattern recognition. Recently, it's started to seem like a metaphor for the state of AI.