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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


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 CEO at Matroid and an Adjunct Professor at Stanford University. His work focuses on Machine Learning, Distributed Computing, and Discrete Applied Mathematics. Reza received his PhD in Computational Mathematics from Stanford under the supervision of Gunnar Carlsson. His awards include a KDD Best Paper Award and the Gene Golub Outstanding Thesis Award. He has served on the Technical Advisory Boards of Microsoft and Databricks.

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. Reza 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. In addition to research, Reza designed and teaches two PhD-level classes at Stanford: Distributed Algorithms and Optimization (CME 323), and Discrete Mathematics and Algorithms (CME 305).