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From Gilles Sadowski <gillese...@gmail.com>
Subject Re: Google Summer of Code 2019 Mentor Registration
Date Tue, 12 Mar 2019 20:28:09 GMT
Hi Eric.

Le mar. 12 mars 2019 à 17:14, Eric Barnhill <ericbarnhill@gmail.com> a écrit :
>
> What I have now found, doing a bit of background research for this, is that
> there is a well-developed pure Java machine learning library called WEKA (
> https://www.cs.waikato.ac.nz/~ml/weka/) . It seems to have good
> institutional support and be well maintained. LIke I had in mind, the
> syntax is pretty intuitive and similar in style to Scikit-Learn. There is a
> nice tutorial using it that can be found at
> https://tech.io/playgrounds/3771/machine-learning-with-java---part-1-linear-regression
> which illustrates this. I don't know what I would want to do differently,
> that Weka hasn't already done, other than its targeting of Java 8. So I
> think it would probably be re-inventing the wheel to try to get something
> similar started here.
>
> I will re-focus my mind on trying to get some momentum for the stats
> functions, which is what I had in mind last summer. I do think if healthy
> momentum can build for stats functions, there is a natural fit for a fair
> amount of machine learning to be incorporated including our own mothballed
> clustering and neural net libraries.

There are also a couple of CM packages that would be worth porting
to [Numbers] or their own component:
  * o.a.c.math4.analysis.integration
  * o.a.c.math4.analysis.interpolation
  * o.a.c.math4.analysis.solvers
(with adaptation to the interfaces of Java 8 "function" package).

As for the "o.a.c.math4.ml" package, it should be fairly easy to
port it to its own component, as there are no dependencies towards
other CM packages.
It could be worth having a small component focused on classification.

WDYT?

Gilles

>
> Eric
>
>
>
>
> On Mon, Mar 11, 2019 at 5:28 PM Bruno P. Kinoshita <kinow@apache.org> wrote:
>
> >  Sounds like an interesting idea Eric. I wonder if we would get some
> > dogfooding through projects like Apache OpenNLP (one that I know uses ML in
> > Java).
> >
> > CheersBruno
> >
> >     On Tuesday, 12 March 2019, 1:24:24 pm NZDT, Eric Barnhill <
> > ericbarnhill@gmail.com> wrote:
> >
> >  On Sat, Mar 9, 2019 at 4:56 PM Gilles Sadowski <gilleseran@gmail.com>
> > wrote:
> >
> > > Hi Eric.
> > >
> > > Le ven. 8 mars 2019 à 22:22, Eric Barnhill <ericbarnhill@gmail.com>
a
> > > écrit :
> > > >
> > > > I am definitely willing to mentor development of the stats libraries
> > as I
> > > > was last year. Now that I work more in data science I am happy to also
> > > > mentor the ML library
> > >
> > > What are you referring to?
> > >
> >
> > Commons-math had a machine learning library. Now that I look it over it is
> > really a bit emaciated. Still, I think there is an opportunity here to get
> > some components up to date that could be pretty widely used, rethinking the
> > structure and grammar of the library to echo Python's highly successful
> > scikit-learn and Keras libraries.
> >
> > There are a lot of young people who are interested in getting into data
> > science, we might get a good candidate or two looking to distinguish
> > themselves. Also Java is such an important language in data science and
> > engineering, even if a lot of the ML model building to date is in R and
> > Python, so it is a great language for someone entering ML to know.
> >
> >
> > > You have to register as a mentor. :-)
> > >
> >
> > Sent.
> >
> >
> > >
> > > Then, read and follow the guidelines:
> > >  http://community.apache.org/guide-to-being-a-mentor.html
> > >
> > > What should be done ASAP is tag existing, or new issues,
> > > with the appropriate label so that tasks will appear here:
> > >    http://s.apache.org/gsoc2019ideas
> >
> >
> > Will do tomorrow, hopefully is not too late.

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