antigravity

8 ms·

1. 1.▲
   by antigravity 18y ago

   Python, then LISP and (SML or Ocaml), then C and assembly and compilers, then Python again. Though I like what Norvig said in http://norvig.com/21-days.html "Use your friends [...] Keep it simple. [...] Play. [...] Given these criteria, m
2. 2.▲
   by antigravity 18y ago

   You mean keep tinkering with the study until it "works"? If you're not careful, you could get http://en.wikipedia.org/wiki/Publication_bias on a massive new scale... It would be interesting to try to find scientifically optimal ways of do
3. 3.▲
   by antigravity 18y ago

   http://catb.org/jargon/html/magic-story.html
4. 4.▲
   by antigravity 18y ago

   (1) Axler's "Linear Algebra Done Right" ...a nice introduction to abstract linear algebra, but not quite abstract or terse enough. (2) These course notes: http://www.math.mcgill.ca/goren/AlgebraII07-08/AlgebraII.htm ...good, though the du
5. 5.▲
   by antigravity 18y ago

   no, yes, yes, yes, no, yes
6. 6.▲
   by antigravity 18y ago

   I'd recommend doing a startup and/or side project involving interesting functions of massive datasets. Technology-wise, at least consider... - learning SML or OCaml or Erlang - learning Python - going deeper into Python. It's a fantastic wa
7. 7.▲
   by antigravity 18y ago

   TextMate, DTerm, MacFusion, Quicksilver, Jumpcut Life without DTerm... why, it seems absurd!