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Inference at Scale with Apache Beam

Offered By: The ASF via YouTube

Tags

Apache Beam Courses Machine Learning Courses Inference Courses GPU Computing Courses Scalability Courses Distributed Computing Courses Model Deployment Courses Data Pipelines Courses Open Source Courses

Course Description

Overview

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Explore how Apache Beam, an open source tool for building distributed scalable data pipelines, can be used to perform common machine learning tasks, with a focus on running inference at scale. Learn about the challenges of deploying models at scale and gain the ability to use Beam to easily parallelize inference workloads. Watch a demo showcasing how Beam can be used to deploy and update models efficiently on both CPUs and GPUs for inference workloads. Gain a high-level understanding of Beam and its applications in machine learning. The 34-minute talk is presented by Danny McCormick, a committer on the Beam project and a senior software engineer at Google, who brings his expertise in open source communities and experience from working on projects like GitHub Actions.

Syllabus

Inference at Scale with Apache Beam


Taught by

The ASF

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