<div dir="ltr">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. <a href="http://orange.biolab.si" target="_blank">http://orange.biolab.si</a><br>
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<div><br></div><div>I was able to train a pile of methods in the <span>gui</span>. Then pickle them to be pulled up later in my scripts to process new streaming data. All in a friendly python add-on. </div>
<div><br></div><div>For some reason it took me a long long time searching to find that package, so I though I'd share.</div><div><br></div><div> <br></div><div>James</div>
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Message: 1<br>
Date: Sun, 28 Apr 2013 12:00:41 -0500<br>
From: Jason Wirth <<a href="mailto:wirth.jason@gmail.com" target="_blank">wirth.jason@gmail.com</a>><br>
To: The Chicago Python Users Group <<a href="mailto:chicago@python.org" target="_blank">chicago@python.org</a>><br>
Subject: [Chicago] Machine learning, all the cool kids are doing it.<br>
Message-ID:<br>
<CAEwvNMgCVOTcBqfWGCc5JDBhWJ=<a href="mailto:w0LV0zfz0eTbCdOzJqYUWrA@mail.gmail.com" target="_blank">w0LV0zfz0eTbCdOzJqYUWrA@mail.gmail.com</a>><br>
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<br>
The Coursera Machine Learning class taught by Andrew Ng at Stanford (<br>
<a href="https://www.coursera.org/course/ml" target="_blank">https://www.coursera.org/course/ml</a>) just started (4/22) and I'm interested<br>
if anyone wants to work through it with me. I've taken this course before<br>
but only got about half way through it before getting busy and "dropping<br>
out."<br>
<br>
<br>
MOOCs are great, but they lack the community needed to have a successful<br>
learning experience. More importantly, learning happens by doing--not by<br>
watching videos--whether it's teaching someone else the material, working<br>
through problems with a partner, or adapting the problems to be relevant<br>
for your projects & internests.<br>
<br>
<br>
One of the downsides about the course is that it uses Octave, not Python.<br>
Despite that we could easily code the problems in Octave, then port them to<br>
Python & Numpy or use equivalent functions in Scikts.learn.<br>
<br>
<br>
So this time around I'm hoping to find someone interested in going through<br>
it together, particularly with a Python focus. Any takers?<br>
<br><span class="HOEnZb"><font color="#888888">
<br>
--<br>
Jason Wirth<br>
<a href="tel:213.675.5294" value="+12136755294" target="_blank">213.675.5294</a><br>
<a href="mailto:wirth.jason@gmail.com" target="_blank">wirth.jason@gmail.com</a><br>
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