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Thursday, May 30 • 3:15pm - 3:45pm
mlpack: or, how I learned to stop worrying and love C++

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mlpack is a general-purpose flexible, fast machine learning library written in C++. The library aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. These algorithms are provided as simple command-line programs, Python bindings (and bindings to other languages), and also C++ classes which can then be integrated into larger-scale machine learning solutions. In this talk I will introduce mlpack and discuss how it achieves its fast implementations via template metaprogramming and by implementing more asymptotically efficient algorithms. Even though C++ is fairly unpopular for machine learning, I will show that it is possible to have easy, understandable, production-quality C++ machine learning code with mlpack. I'll also give some examples of usage, including how we use mlpack inside of RelationalAI, and also talk about the future goals and development of the library.

avatar for Ryan Curtin

Ryan Curtin

Computer Scientist, Relational AI
Ryan Curtin is a Computer Scientist at RelationalAI.  His Ph.D. work at Georgia Tech focused on fast machine learning algorithms.  These algorithms are the basis of the mlpack C++ machine learning library, which he has maintained for nearly a decade. 

Thursday May 30, 2019 3:15pm - 3:45pm CDT
(G) P1808 Normandale Partnership Center, 9700 France Ave So, Bloomington, MN 55431