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Wednesday, June 21 • 3:40pm - 4:16pm
Flux: Machine Learning with Julia

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Flux.jl is a new Julia package for machine learning. It aims to provide strong tooling and support for debugging, high-level features for working with very complex networks, and state of the art performance via backends like TensorFlow or MXNet, while also providing a very high level of interoperability so that approaches can easily be mixed and matched. This talk will introduce Flux from the ground up and demonstrate some of its more advanced features.


Mike Innes

Julia Computing, Inc.
I work with Julia Computing on Julia's IDE, Juno, as well as various projects within the machine learning ecosystem.

Wednesday June 21, 2017 3:40pm - 4:16pm
East Pauley Pauley Ballroom, Berkeley, CA