Here are a few resources that I have come across. I am not in any way endorsing these as correct. I am merely listing ones I find interesting, partly so that I can browse them as I have time.
I am not updating this page anymore,
For a nice listing of free textbooks, see section 5.1.3 of our UTMOST CCLI grant proposal.
* A Better Calculator is a really cool javascript graphing calculator.
Here are a few free calculus textbooks.
The following OpenCourseWare courses seem like they overlap with our numerical analysis course:
Here are a few other course outlines:
* http://www.math.yorku.ca/SCS/Gallery/ – Good and misleading graphs (look at the Ithaca Times example on http://www.math.yorku.ca/SCS/Gallery/context.html!)
* Probabilistic Programming and Bayesian Methods for Hackers - based on Python and uses a lot of cool examples.
Here are some very specialized packages for computing in linear algebra.
* MacTutor Archive - This is probably one of the best web references on math history.
Here are some great resources for learning scientific python:
Here are some general Python resources
* I am constantly referencing The Short Math Guide For Latex.
* http://freedomdefined.org/Licenses/NC An essay arguing why the noncommercial restriction for Creative Commons licenses is bad.
Mathematician: noun, someone who disavows certainty when their uncertainty set is non-empty, even if that set has measure zero.
99 instances of bugs in the code... 99 instances of bugs, .... code one out, mark it out (without running full tests), 106 instances of bugs in the code... 106 instances of bugs in the code... 106 instances of bugs, ....
(from here)
A tongue-in-cheek history of computer languages.
Walking on water and developing software from a specification are easy if both are frozen.
Here are a few good resources for analyzing numbers and sequences.
Here are some interesting-looking ipod apps that I might try someday.