[Chicago] Machine learning, all the cool kids are doing it.

James Bittner jamesbittner+chipy at gmail.com
Mon Apr 29 23:12:20 CEST 2013

I had a project a year ago that required using machine learning from a
sensor network data feed. I was really impressed with the python
script-able Orange machine learning/data visualization frame work.

I was able to train a pile of methods in the gui. Then pickle them to be
pulled up later in my scripts to process new streaming data. All in a
friendly python add-on.

For some reason it took me a long long time searching to find that package,
so I though I'd share.


Message: 1
> Date: Sun, 28 Apr 2013 12:00:41 -0500
> From: Jason Wirth <wirth.jason at gmail.com>
> To: The Chicago Python Users Group <chicago at python.org>
> Subject: [Chicago] Machine learning, all the cool kids are doing it.
> Message-ID:
>         <CAEwvNMgCVOTcBqfWGCc5JDBhWJ=
> w0LV0zfz0eTbCdOzJqYUWrA at mail.gmail.com>
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> The Coursera Machine Learning class taught by Andrew Ng at Stanford (
> https://www.coursera.org/course/ml) just started (4/22) and I'm interested
> if anyone wants to work through it with me. I've taken this course before
> but only got about half way through it before getting busy and "dropping
> out."
> MOOCs are great, but they lack the community needed to have a successful
> learning experience. More importantly, learning happens by doing--not by
> watching videos--whether it's teaching someone else the material, working
> through problems with a partner, or adapting the problems to be relevant
> for your projects & internests.
> One of the downsides about the course is that it uses Octave, not Python.
> Despite that we could easily code the problems in Octave, then port them to
> Python & Numpy or use equivalent functions in Scikts.learn.
> So this time around I'm hoping to find someone interested in going through
> it together, particularly with a Python focus. Any takers?
> --
> Jason Wirth
>     213.675.5294
>     wirth.jason at gmail.com
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