On Fri, May 10, 2024 at 04:42:49PM +0200, Ralf Gommers wrote:
> It gets ever-easier to install new Python versions, with pyenv/conda/etc. The
> "my single Python install comes from python.org and I'm using the same one
> because I am afraid to upgrade" is much less of an issue than it was 10
On Tue, May 07, 2024 at 11:31:02AM +0200, Ralf Gommers wrote:
> make `pip install scikit-image==0.22` work if that version of scikit-image
> depends on an unconstrained numpy version.
Would an option be for the scikit-image maintainers to release a version of
scikit-image 0.22 (like 0.22.1)
lections), you might know people who could
benefit from this course to learn machine learning. Please help us spread the
word.
Pythonly yours,
Gaël
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Gael Varoquaux
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Thanks. Exactly what I needed. I don't know why I did not find it myself
:).
Cheers,
Gaël
On Wed, Jan 22, 2020 at 05:02:01PM +0100, Ralf Gommers wrote:
> On Wed, Jan 22, 2020 at 1:13 AM Gael Varoquaux
> wrote:
> Did someone tweet about this, so that I retweet? I'm happy
> https://mail.python.org/mailman/listinfo/numpy-discussion
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> The one thing I worry about is maintenance burden, where numpydoc is already
> spread a little bit thin -- would any of the Pandas developers be willing to
> maintain it?
Any reason that this is not done in sphinx, with the napoleon extension?
On Mon, May 20, 2019 at 11:01:15AM -0700, Nelle Varoquaux wrote:
> I'm pretty sure not all funding is acknowledged on scikit-learn's frontpage. I
> think the minimum amount to be acknowledge with a logo is funding for a full
> time developer for at least a year, ie at least 100k€.
These days,
il.python.org/mailman/listinfo/numpy-discussion
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On Tue, Jul 03, 2018 at 09:42:08AM +0200, Andrea Gavana wrote:
> I’m happy if you feel better after your tirade.
Not really. I worry a lot that many users are going to be surprised when
Python 2 stops being supported, which is in a couple of years. I wrote
this tirade not to make me feel better,
On Tue, Jul 03, 2018 at 08:54:51AM +0200, Andrea Gavana wrote:
> This sound so very powerful... it’s such a pity that these type of gems won’t
> be backported to Python 2 - we have so many legacy applications smoothly
> running in Python 2 and nowhere near the required resources to even start
>
On Mon, Jul 02, 2018 at 05:31:05PM -0600, Charles R Harris wrote:
> ISTR that some parallel processing applications sent pickled arrays around to
> different processes, I don't know if that is still the case, but if so, no
> copy
> might be a big gain for them.
Yes, most parallel code that's
While we are in the crazy wish-list: having dtypes that are universal
enough for pandas to use them and export their columns with them would be
my crazy wish. I hope that it would help adding more uniform support for
things like categorical variables in the pydata ecosystem.
Gaël
> The other packages are nice but I would really love to just use scipy/
> sklearn and have decompositions, factorizations, etc for big matrices
> go a little faster without recoding the algorithms. Thanks
If you have very big matrices, scikit-learn's PCA already uses randomized
linear algebra,
Another point in defence of vstack vs stack/concatenate: last time I
looked, it was faster on smallish arrays.
Gaël
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s now 'array([True])' instead of
> >> 'array([ True])'.
> >> Allan
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knowledge and the opportunity to go ahead and organize a similar
> workshop in any conference they go to.
> Jaime
> P.S. I also got a chance to catch up with Francesc Alted and Travis Oliphant,
> which is always great!
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Gael Varoquaux
Researcher, INRIA Parietal
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