| Talk | |
|---|---|
| Talk Title | Numerical Computing in Python |
| Speaker |
Rahul Agrawal
|
| Level | Moderate |
| Category | Normal talk (45 - 60 minutes) |
| Accepted | False |
| Scheduled | False |
| Presentation Materials | Presentation materials have not yet been added |
| Abstract | Modern day computing algorithms require processing of large quantities of data. Such number crunching capabilities are usually slow if coded in pure Python. However with a suitable set of extensions, one can have the best of both worlds - convenience of Python and the speed nearing those of Fortran or C code. In this talk, we will try to discuss options available for numerical computing in Python along with a demonstration of few applications. |
| Rating | Score: 7 from 7 ratings |
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This talk has 4 comments.
Comments:
will this include the GNU-R interface to python or is it just numpy?... you will explain about numpy.. right?..
In the talk will try to cover numpy, scipy primarily with actual data mining task demo. Have plans of adding the GNU-R interface to it given the popularity of R. Am working on the stuff over this week to arrive at a decent trade off between depth of coverage of one technology and the coverage of different options...
Would you also like to consider SymPy http://docs.sympy.org/? which provides an extensive framework for Symbolic computation in Python something which is the forte of Mathematica. ..
Rahul, you could contrast the features you have lined up with those provided by matlab,scilab etc. It would be great !..
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