Inference at Scale with Apache Beam
Offered By: The ASF via YouTube
Course Description
Overview
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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