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Wednesday, June 21 • 4:52pm - 5:28pm
Modern Machine Learning in Julia with TensorFlow.jl

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By many measures, TensorFlow has grown over the last year to become the most popular library for training machine-learning models. TensorFlow.jl provides Julia with a simple yet feature-rich interface to TensorFlow that takes advantage of Julia's multiple dispatch, just-in-time compilation, and metaprogramming capabilities to provide unique capabilities exceeding TensorFlow's own native Python API. This talk will demonstrate TensorFlow.jl by guiding listeners through training a realistic model of image captioning , showing how to 1) construct the model with native Julia control flow and indexing, 2) visualize the model structure and parameters in a web browser during training, and 3) seamlessly save and share the trained model with Python. No prior experience with TensorFlow is assumed.


Speakers
JM

Jonathan Malmaud

MIT
Ph.D. candidate at MIT studying artificial intelligence


Wednesday June 21, 2017 4:52pm - 5:28pm
East Pauley Pauley Ballroom, Berkeley, CA