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Tuesday, August 18 • 11:00am - 11:40am
Economical machine learning via functional programming

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Machine learning technologies play an important role in modern software systems, especially as a complement to platforms capable of supplying abundant training data. However, machine learning is notoriously difficult to work with from a software engineering perspective, compounding existing technical debt with new sources of uncertainty and complexity. Technical debt management is therefore crucial when using machine learning, placing a premium on basic correctness, minimization of accidental complexity, and abstractions about which one can easily reason. Fortunately, functional programming ideas can help us achieve these goals. We will discuss how functional programming design patterns can be applied to machine learning and data processing problems, with examples using Scala and the Scalaz library.

Speakers
avatar for David Andrzejewski

David Andrzejewski

Data Sciences Engineer, Sumo Logic
David Andrzejewski is a Data Sciences Engineer at Sumo Logic and co-organizer of the SF Bay Area Machine Learning meetup group. Prior to Sumo Logic, David held a postdoctoral research position working on knowledge discovery at Lawrence Livermore National Laboratory (LLNL). He completed his PhD in Computer Sciences at the University of Wisconsin-Madison in 2010, where he had also previously received an M.S. in Computer Sciences and a B.S. in... Read More →


Tuesday August 18, 2015 11:00am - 11:40am
Track A

Attendees (23)