Lecture 4: Transforms (20)
matthewlee626

These rotations remind me of some of the concepts illustrated by the SVD decomposition. See slide 5 on https://eecs189.org/docs/lec13.pdf, where a base unit vector gets stretched and rotated along some axes. Those transformations are also represented by the matrices we see in these slides!

jerrymby

The fact that a rotation matrix is an orthogonal matrix can be pretty handy. We can simply take the transpose as it's inverse, which can save us a lot of time when we are working with rotation matrices.

llejj

One cool thing about orthogonal matrices is they don't stretch or squish space

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