Hi David - I try to teach workshops at a level<br>where if you know a bit of programming and<br>a bit of mathematics, then you can get some<br>intuition and start working with data. But... there's<br>always a learning curve!<br>
<br>Regardless, I'm sitting in the Church room right<br>now, you should stop in.<br><br> mike<br><br><br><br><div class="gmail_quote">On Thu, Jan 19, 2012 at 4:11 PM, David Knupp <span dir="ltr"><<a href="mailto:knupp@well.com">knupp@well.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi all,<br>
<br>
Just an brief introduction, and a question. I'm developing an interest in machine learning, but I'm pretty much a complete ML newbie. I started trying to take the class being offered by Stanford last quarter, but the insanity of the holidays plus various end-of-year job-related deadlines all combined to make it pretty much a hopeless venture. I have much higher hopes this next time around. (I believe the class starts up again on the 23rd.)<br>
<br>
I'm an artist-turned-QA engineer by day, and fairly handy with python and perl, though I don't have any experience with R. I don't have an extensive math background, but I didn't find the math in the ML class too hard to follow along with.<br>
<br>
I don't know what kind of things this group covered in the past. I'm wondering whether there's a place of the uninitiated like myself.<br>
<br>
In any event, I may try to stop by this evening.<br>
<br>
Thanks,<br>
--d.<div class="HOEnZb"><div class="h5"><br>
<br>
<br>
On Thu, 19 Jan 2012, Mike Schachter wrote:<br>
<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
Hey everyone, I'll be 15-30 minutes late to the ML meetup<br>
tonight. See you then (by 7:00pm)!<br>
<br>
mike<br>
<br>
<br>
On Mon, Jan 16, 2012 at 6:03 PM, Mike Schachter <<a href="mailto:mschachter@eigenminds.com" target="_blank">mschachter@eigenminds.com</a>> wrote:<br>
Hello everyone!<br>
<br>
I'm keen on restarting the machine learning<br>
meetups this year. Here's our wiki page for<br>
the uninitiated:<br>
<br>
<a href="https://www.noisebridge.net/wiki/Machine_Learning" target="_blank">https://www.noisebridge.net/<u></u>wiki/Machine_Learning</a><br>
<br>
My focus on data this year will be sound<br>
and government&census data, and applications<br>
relevant to Noisebridge itself.<br>
<br>
Sound because I work with brain cells in the auditory<br>
system, and government data because there's<br>
a potential treasure trove of very relevant machine<br>
learning applications for data accessible online,<br>
with potential to for helping our crumbling democracy<br>
and such.<br>
<br>
So this Thursday, 6:30pm, in either the Church<br>
or Turing room, come over and help me brainstorm<br>
some ideas for datasets to work with. Next week<br>
I'm going to teach a workshop on Random Forests<br>
in R.<br>
<br>
Some sites with datasets I'm looking through:<br>
<br>
<a href="http://fec.gov/" target="_blank">http://fec.gov/</a><br>
<a href="http://www.opensecrets.org/" target="_blank">http://www.opensecrets.org/</a><br>
<a href="http://opengovernment.org" target="_blank">opengovernment.org</a><br>
<a href="http://thomas.loc.gov" target="_blank">http://thomas.loc.gov</a><br>
<a href="http://openstates.org/" target="_blank">http://openstates.org/</a><br>
<a href="http://www.votesmart.org/" target="_blank">http://www.votesmart.org/</a><br>
<a href="http://www.opencongress.org/" target="_blank">http://www.opencongress.org/</a><br>
<a href="http://www.govtrack.us/" target="_blank">http://www.govtrack.us/</a><br>
<a href="http://www.census.gov" target="_blank">http://www.census.gov</a><br>
<br>
<br>
<br>
</blockquote>
</div></div></blockquote></div><br>