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SUMMARY:Thinking in arrays - Jim Pivarski
DTSTART;TZID=America/Chicago:20230711T080000
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DTSTAMP:20261007T034331Z
UID:pretalx-2023-XBUC8S@cfp.scipy.org
DESCRIPTION:Despite its reputation for being slow\, Python is the leading 
 language of scientific computing\, which generally needs large-scale (fast
 ) computations. This is because most scientific problems can be split into
  "metadata bookkeeping" and "number crunching\," where the latter is perfo
 rmed by array-oriented (vectorized) calls into precompiled routines.\n\nTh
 is tutorial is an introduction to array-oriented programming. We'll focus 
 on techniques that are equally useful in NumPy\, Pandas\, xarray\, CuPy\, 
 Awkward Array\, and other libraries\, and we'll work in groups on three cl
 ass projects: Conway's Game of Life\, evaluating decision trees\, and comp
 utations on ragged arrays.
LOCATION:Classroom 101
URL:https://cfp.scipy.org/2023/talk/XBUC8S/
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