[Chicago] ChiPy October 8th Meeting

[Joe Jasinski]

Hi all,

ChiPy has an excellent talk lineup this Thursday.  We are meeting at Loyola
University at the address below.

*Where:*
Loyola University
Philip H. Corboy Law Center
<https://www.google.com/maps/place/Philip+H.+Corboy+Law+Center/@41.8973803,-87.6271242,17z/data=!3m1!4b1!4m2!3m1!1s0x880fd352f4ca48bf:0x45b3bb60ee4f6313>
Room number 209
25 E Pearson St
Chicago, IL 60611


*When:*
Thursday October 8th, 7:00pm

*How:*
You can rsvp at chipy.org or via our Meetup
<http://www.meetup.com/_ChiPy_/> group.


*What:*


   - *Python-fu in the GIMP*
   (0:25:00 Minutes)
   By: Tanya Schlusser
   GIMP (the GNU Image Manipulation Program) is great all by itself but is
   even better with Python-fu. This talk demonstrates a little Python-fu to
   manipulate images in GIMP.
   - *Factor analysis: simplifying high dimensional data sets for
   visualization and machine learning*
   (0:25:00 Minutes)
   By: Mark Albert
   For many machine learning problems, there are far more dimensions to our
   data than there need to be for efficient learning. Often a first step is
   dimensionality reduction to remove both redundancy and noise. In addition
   to more efficient automated learning, factor analysis allows us to
   visualize high dimensional data sets in our standard human-limited 2 or 3
   dimensions. For demonstration, we will apply PCA on a set of questions
   asked of the audience to map everyone onto a 2D "personality" map -
   allowing us to visualize the underlying personality factors of those
   present. Beyond fun visualizations, these techniques are the basis of more
   efficient generalization in many machine learning problems.
   - *Fancy genetics and simple scripts: Manipulating DNA data and becoming
   more proficient with Python*
   (0:20:00 Minutes)
   By: Mark Mandel
   Our ability to read the genetic code of organisms and to use DNA
   sequencing to learn new biology has benefited tremendously from
   technological advances in the past ten years. My lab looks at how animals
   get colonized with specific bacteria. As we have been generating more data
   it has become clear that we are underutilizing the information. We are
   beginning to build resources to be more efficient and clever at data
   processing and data mining from biological samples. I'll talk a little
   about the science in the lab and show one of our Python projects that is
   functional but in its early stages. I am eager for feedback, and I think
   the talk will have resonance for a new motivated Python user in any field.


You can find more information about ChiPy at our website
http://www.chipy.org/

We hope to see you there!

Joe
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