Long before, I studied strang's linear algebra book with MIT video lectures. It was good and well designed course which I liked, but it is a bit prescriptive and I am having difficulties with LA.
I read books on computer graphics, vision, machine learning and will read books on convex optimization linear dynamical systems etc. which both apply and use theory of LA.
But I am having difficulties truly understanding these concepts with my LA level. So I need a book strong at theory and geometric intuition of LA. I know how can I find eigen vector but I am not sure what exactly it does, I don't exactly know what affine transform is, and never exposed to rigoruous definition of vector space all I know is orthogonal bases and projection, basis changing etc..
The books I plan to read are hoffman kunze and after that axler's LA done right.
Are these the books which I need or do you recommend ones which are good for above mentioned needs ?
I am currently reading baby rudin so I am mostly okey with proofs.