2012/11/15 Gael Varoquaux <[email protected]>:
> scikit-learn integrates machine learning algorithms in the tightly-knit
> scientific Python world, building upon numpy, scipy, and matplotlib. It
> provides simple, efficient and effective data mining solutions,
> accessible to everybody and reusable in various contexts. Our aim is to
> provide a machine-learning module that is a versatile tool for science
> and engineering in any discipline.
I'm not sure if we should put "data mining solutions" in there. For
me, "data mining" carries the connotation of database integration,
unsupervised, exploratory algorithms and recommender systems, while
"solutions" is a bit of a business term ("reads your webserver logs,
visualizes them and magically suggests advertising strategies").
May I suggest instead of the final two sentences:
"It is a Python library [or toolkit?] offering efficient
implementations of common and advanced algorithms through a consistent
API, reusable for various tasks in science and engineering."
As for classic vs. recent -- I'm happy if both were put in, though I'd
prefer "state of the art" to "recent".
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
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