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September 17-18, 2017: Training
September 18-20, 2017: Tutorials & Conference
San Francisco, CA

Scaling CNNs with Kubernetes and TensorFlow

Reza Zadeh (Matroid | Stanford)
4:00pm–4:40pm Tuesday, September 19, 2017
Location: Imperial B
Average rating: ****.
(4.00, 1 rating)

What you'll learn

  • Explore Matroid’s pipeline, which uses TensorFlow, Kubernetes, and Amazon Web Services

Description

Reza Zadeh presents a Kubernetes deployment on Amazon AWS that provides customized computer vision to a large number of users. Reza offers an overview of Matroid’s pipeline, which uses TensorFlow, Kubernetes, and Amazon Web Services, and explains how Matroid allows customization of computer vision neural network models in the browser, followed by building, training, and visualizing TensorFlow models, which are provided at scale to monitor streams of video.

Photo of Reza Zadeh

Reza Zadeh

Matroid | Stanford

Reza Bosagh Zadeh is founder and CEO at Matroid and an adjunct professor at Stanford University, where he teaches two PhD-level classes: Distributed Algorithms and Optimization and Discrete Mathematics and Algorithms. His work focuses on machine learning, distributed computing, and discrete applied mathematics. His awards include a KDD best paper award and the Gene Golub Outstanding Thesis Award. Reza has served on the technical advisory boards of Microsoft and Databricks. He is the initial creator of the linear algebra package in Apache Spark. Through Apache Spark, Reza’s work has been incorporated into industrial and academic cluster computing environments. Reza holds a PhD in computational mathematics from Stanford, where he worked under the supervision of Gunnar Carlsson. As part of his research, Reza built the machine learning algorithms behind Twitter’s who-to-follow system, the first product to use machine learning at Twitter.