Math 4242 Resources
Software
Computation is at the heart of applications of linear algebra. This
course will not require you to work with software, but I encourage you to
experiment with computation on your own. You're welcome to come chat with me
about what you are doing.
Here are some resources for computation:
Matlab is a simple programming languange and
development environment designed with efficient matrix comptations in
mind. It is a standard and very convenient option for doing matrix
comptations and for rapid prototyping of computational mathematics
software. Matlab is commercial software. Rick Moeckel, who has taught Math 4242 several times, has written two
"labs" to get you started with linear algebra computations in Matlab, available
here and
here.
I am told that
Python is a good choice of language for scientific
computing (amongst other things). If you want to try out Python for
scientific computing, I suggest you start here.
Fo some discussion of advantages
of Python over Matlab, see here and
here.
LAPACK is a standard library for fast, large-scale matrix computations.
Books
The Meyer book is very nice, but there are some other nice
books out there with different advantages. Here are two:
Axler, Linear Algebra Done Right. Emphasizes linear transformations and
largely avoids matrices. Math majors and those in interested theory may
enjoy taking a look at this book.
Trefethen and Bau, Numerical Linear Algebra. This focuses on
computatation. It is very readable, but is pitched
at a somewhat higher level than Meyer. It'd be a very pleasant read once
you've finished most of this course.