Apache: Big Data Europe 2016
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Monday, November 14 • 16:30 - 17:20
Deep Neural Network Regression at Scale in Spark MLlib - Jeremy Nixon, Spark Technology Center

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Deep Neural Network Regression at scale in Spark MLlib - Jeremy Nixon will focus on the engineering and applications of a new algorithm in MLlib. The presentation will focus on the methods the algorithm uses to automatically generate features to capture nonlinear structure in data, as well as the process by which it's trained. Major aspects of that are the compositional transformations over the data, advantages of the various  activation functions, the final linear layer, the cost function and training via backpropagation. Applications will look into how to use neural network regression to model data in computer vision, finance, and the environment. Details around optimal preprocessing, the type of structure that can be found, and managing its ability to generalize will inform developers looking to apply nonlinear modeling tools to problems that they face. 

avatar for Jeremy Nixon

Jeremy Nixon

Machine Learning Engineer, Spark Technology Center
"I'm a Machine Learning Engineer at the Spark Technology Center, focused on scalable deep learning. I contribute to MLlib at the STC, which I joined after graduating from Harvard College concentrating in Applied Mathematics and Computer Science.

Monday November 14, 2016 16:30 - 17:20 CET
Giralda VI/VII