Bayesian Modeling & Python Data Tools Tues. March 19 @6pm

For folks unable to attend in-person, register to attend the event and two (2) hours before the event we will email you a link to watch the event via live webcast.

 

University of Colorado Denver - Tuesday March 19, 2013 @ 6:00pm MST
Large auditorium (170 person capacity) with 20' screen.

Location: CU Denver - North Classroom #1539 - 1200 Larimer Street
Denver, CO[masked] - Map: http://bit.ly/Tyznzg

Agenda:

6:00 - 6:15 Schmooze - Old Chicago Pizza will be served.

6:15 - 7:15 Bayesian Modeling by Mark Labovitz

7:15 - 8:30 Python Data Tools by Cary Miller

8:30 - 9:30 Network at Old Chicago at 14th and Market.
See: http://www.oldchicago.com/denver-market-street

Bayesian Modeling, Inference, Prediction, and Decision-Making - Abstract

Uncertainty -- a state of incomplete information -- is pervasive yet we often must make key decisions based on imperfect information. The Bayesian statistical approach to uncertainty quantification, which involves combining information, both internal and external to your available data sources, into an overall information summary, is both logically internally consistent and simple to describe: there's one equation for inference (drawing valid conclusions about the underlying data-generating process), one for prediction of observables, and one for optimal decision-making.

However, specifying the ingredients that, when combined, formulate a good model for your uncertainty is a process -- combining elements of both art and science, intuition and rigor -- that can take a lifetime to master.

Mark Labovitz, an independent data scientist, will provide a brief overview of Bayesian Probability Theory and important technologies. Mr. Labovitz has over thirty (30) years experience as a Statistical / Quantitative Analyst and Team Lead specializing in the quantitative analysis of financial and marketing data. He has an MBA from University of Pennsylvania, The Wharton School and two (2) PhD's: Geomathematics – The Pennsylvania State University; and Applied Mathematics [masked]), Concentration in Statistics– University of Colorado Denver.

Python Data Tools - Abstract

Python is a high-level programming language designed for ease-of-use, speed, readability and tailored for data-intensive applications. Python supports multiple programming paradigms, including object-oriented, imperative and functional programming styles. It features a fully dynamic type system and automatic memory management, similar to that of Scheme, Ruby, Perl and Tcl.

Simply, Python is easy to learn, platform neutral and cheap. Python is a tool to build other tools with, including data analysis tools. It was actually conceived in a huge orgy of different programming paradigms, styles and languages.

This presentation covers the nuts and bolts of manipulating, processing, cleaning and crunching data in Python:

Learn basic and advanced NumPy (Numerical Python) features
Examples of using Python for analyzing large data with emphasis on concurrency
Different techniques in concurrency and when each is appropriate
Analyze streaming Twitter feeds using Python data tools such as pandas and The Natural Language Toolkit
Make these tools go fast for massive data sets using state-of-the-art Python concurrency techniques; multiprocessing, coroutines and greenlets
Use high-performance tools to load, clean, transform, merge, and reshape data Measure data by points in time, whether it’s specific instances, fixed periods, or intervals

Cary Miller, a long-time Python programmer, is a data scientist / open source programmer who has worked with data in many commercial and academic settings. He earned an MS in Applied Mathematics from the University of Colorado Denver. Mr. Miller currently works in litigation support at Catalyst Repository Systems in downtown Denver. He has a wide-ranging data background including work in the health care, energy, financial and bioinformatics sectors.

Join or login to comment.

  • Dave D.

    The meetup was really good and very useful. However, one speaker went extremely fast (and assumed a strong background in probability modeling & nomenclature), while the other speaker went extremely slow an assumed no prior experience with Python. I think somewhere in the middle (for both speakers) would've been perfect. That being said, I learned a lot from both speakers... just not exactly what I needed to.

    March 22, 2013

  • Tom R.

    Good, I got a few key questions I had about Bayesian inference answered.

    March 21, 2013

  • Michael M.

    Raw video is now available at
    http://www.ustream.tv/channel/bayesian
    We'll be moving it to YouTube in a couple of weeks. We'll be posting the slides in a couple of days.

    2 · March 20, 2013

  • Carey G. B.

    Be sure to let us know where the videos get posted (YouTube, Vimeo,...)

    March 20, 2013

  • zheng z.

    Will the video be available online?

    1 · March 20, 2013

  • Larry R.

    Webcast was great to have, audio a little rough. Sorry to miss out on the before and after schmoozing though.

    March 19, 2013

  • Michael W.

    I respectfully ask that you take 20 minutes after the event and walk 2 blocks to Old Chicago for a drink / bite. Network and support our sponsor, Old Chicago.

    March 19, 2013

    • Michael M.

      I will this time :-)

      March 19, 2013

    • Dave D.

      Sorry I had to take off early. Thanks for setting this up. I learned a lot of what I needed and will join you again.

      March 19, 2013

  • Bryan L.

    Cant make it tonight

    March 19, 2013

  • Shane K.

    Won't be able to make this one, but interested in the webcast.

    March 19, 2013

  • Michael W.

    March 19, 2013

  • Hunter T.

    scheduling conflict. :(

    March 19, 2013

  • Kurt Harriger (.

    going to be a bit late, but Ill catch what I can.

    March 19, 2013

  • Rachel E

    have to listen in

    March 19, 2013

  • Michael W.

    Will email and post link at 4pm MST today.

    Just come listen / ask questions / discuss / network.

    March 19, 2013

  • Dave D.

    Looking forward to this. What's the standard protocol? Bring a machine or just listen/ discuss?

    March 18, 2013

  • Jeffrey O.

    Will connect to live stream for part of it. Hoping to catch a recording of it for the remainder.

    March 18, 2013

  • Nancy A

    Looking forward to attending.

    February 25, 2013

  • Dru W.

    Is there any hope for any more meetings up north off the Turnpike for all those emotionally scarred people like me too scared to venture down into Denver where all those millions cars immediately surrounding you, cops attempt to ticket you and the perpetual hunt for extinct over-priced parking spots (to become the prey of predatory tow trucks)? Come north I pray you -- where the quantity cows exceeds the condos and you can still hug a prairie dog in Boulder (with enough doxycyline).

    2 · February 21, 2013

    • Rangarajan

      Dru ! Read my mind .. thank you !

      February 21, 2013

    • Dru W.

      Addendum: I don't think it should be in Boulder -- hell, Boulder can be scarier than Denver -- the Parking Gestapo (now hi-tech with mobile cams) around Pearl St. is worse (more competent) than Denver and having to stop at the blinking cross walks and worship and wait on the pedestrians is well .... No, not Boulder, but that vast wasteland between Boulder and Denver has lots of options and easy to get to. And, yes there should ALSO be meeting in the DTC -- I just won't go to them as don't go to downtown Denver.

      1 · February 21, 2013

  • Michael M.

    Thank you for scheduling on a Tuesday!

    February 21, 2013

  • Tom R.

    Can't wait. Very excited for this one.

    February 21, 2013

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Rafaël

We just grab a coffee and speak French. Some people have been coming every week for months... it creates a kind of warmth to the group.

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