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NET Machine Learning: F# and Accord.NET
Recorded at:

by Alena Hall on Mar 19, 2016 | NOTICE: The next QCon is in San Francisco Nov 7-11, 2016. Join us!
45:03

Summary
Alena Hall presents various machine learning algorithms available in Accord.NET - a framework for machine learning and scientific computing in .NET. Hall also takes a look at sample types of problems to see how we can apply machine learning algorithms using the Accord.NET framework with the F# functional approach.

Bio

Alena Dzenisenka is a young researcher in the field of theoretical mathematical abstractions and innovative algorithmic models possible in modern programming concepts. She is a member of F# Software Foundation Board of Trustees. Alena currently works as a Software Architect and has more than 10 years of professional experience including complex distributed systems and cloud computing.

Software is Changing the World. QCon empowers software development by facilitating the spread of knowledge and innovation in the developer community. A practitioner-driven conference, QCon is designed for technical team leads, architects, engineering directors, and project managers who influence innovation in their teams.

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