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April 10-11, 2018: Training
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Beijing, CN

Scaling convolutional neural networks with Kubernetes and TensorFlow

This will be presented in English.

Reza Zadeh (Matroid | Stanford)
11:1511:55 Thursday, April 12, 2018
Secondary topics:  AI应用的硬件、软件栈(Hardware and Software stack for AI applications), 计算机视觉(Computer Vision)


Reza Zadeh offers an overview of Matroid’s Kubernetes deployment, which provides customized computer vision and stream monitoring to a large number of users, and demonstrates how to customize computer vision neural network models in the browser. Along the way, Reza explains how Matroid builds, trains, and visualizes TensorFlow models, which are provided at scale to monitor video streams.

Reza Zadeh将会概述Matroid的Kubernetes部署方案。它能为海量用户规模的计算机视觉和流监控提供定制化。他还会展示如何在浏览器中定制计算机视觉的神经网络模型。 在此过程中,Reza还将解释Matroid如何构建、训练和可视化的大规模监视视频流的TensorFlow模型。

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.