On Thu, Nov 15, 2012 at 8:21 PM, Lars Buitinck <[email protected]> wrote:
> 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").
>
+1
>
> 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".
>
"well-known algorithms" would do the trick too.
Mathieu
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