ChicagoRuby: Downtown - Fast Iteration on Machine Learning Development

Topic: Fast Iteration on Machine Learning Development Using Convention Over Configuration
Machine learning and data science has long suffered from a mentality of hacking together multiple tools using collections of scripts to quickly narrow down the correct model for a predictive analytics question. The onus becomes on a software or data engineering team to implement the solution in a clean, scalable and maintainable way. We explore an approach where development equals production and interactive experimentation in R results in a production-ready classifier, with strong inspirations from the Ruby community.

About the Presenter
Robert Krzyzanowski (http://homepages.math.uic.edu/~robertk/) obtained his undergraduate degree in mathematics, computer science,and physics from North Central College, a private liberal arts college in Naperville, before moving to graduate studies in pure mathematics at the University of Illinois at Chicago. In his spare time, Rob is a fan of chess and cooking. Professionally he started as a Rails developer at Avant (http://avant.com), quickly transitioning to fusing Ruby and R through data science and now serves as director of data engineering, helping a team of thirty data scientists and engineers solve a multitude of predictive analytics questions in risk, fraud, and marketing.

After most downtown meetings we head over to Elephant & Castle (185 N. Wabash) for refreshments & fellowship. Join us for a few minutes if you have time.

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WindyCityRails
Level up your skills. WindyCityRails is Chicago's Ruby on Rails conference, happening in September.
Details: http://windycityrails.org (http://windycityrails.org/)