Machine Learning in the Open

*
Accepted Session
Long Form
Intermediate
Scheduled: Tuesday, June 26, 2012 from 10:00 – 11:45am in B304

Excerpt

Machine learning and data mining methods underlie many exciting products and services, but their underlying workings remain opaque to many, even developers. I will provide a brief tutorial on some of the most important concepts and methods from machine learning and data mining, with motivating examples and illustrations from open source tools. Particular emphasis will be placed on learning methods and their appropriate use.

Description

There is nothing more practical than a good theory.- Variously attributed

Machine learning and data mining methods underlie many exciting products and services, but their underlying workings remain opaque to many, even developers. I will provide a brief tutorial on some of the most important concepts and methods from machine learning and data mining, with motivating examples and illustrations from open source tools.

Topics will include data exploration, data preparation, supervised and unsupervised learning methods (including models, patterns, scoring functions, optimization, and search), performance tests, and model evaluation. Particular emphasis will be placed on learning methods and their appropriate use.

Speaking experience

* I presented at last year's OSB, "Data Science in the Open":http://opensourcebridge.org/sessions/688.
* I have presented at professional conferences before (at CMU, ANU, and Stanford).
* I regularly give presentations in the workplace and at meetup groups.

Speaker

  • Johntaylor

    John Taylor

    iovation

    Biography

    John L. Taylor works as a Senior Data Analyst at iovation and is a member of PDX R Users and PDX Hadoop/Data Science Groups. Formerly, he was a graduate student in Logic and Computation at CMU and has BAs in philosophy and psychology.

    John is, in no particular order and among other things, an aspiring polymath, intellectual magpie, cultural gadfly, father and husband, data geek, plain-old-geek, bibliophile, pop cultural glutton, recreational mathematician, and skeptic.

    Sessions

      • Title: Machine Learning in the Open
      • Track: Cooking
      • Room: B304
      • Time: 10:0011:45am
      • Excerpt:

        Machine learning and data mining methods underlie many exciting products and services, but their underlying workings remain opaque to many, even developers. I will provide a brief tutorial on some of the most important concepts and methods from machine learning and data mining, with motivating examples and illustrations from open source tools. Particular emphasis will be placed on learning methods and their appropriate use.

      • Speakers: John Taylor