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Scaling and Unifying SciKit Learn and Spark Pipelines using Ray

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How Ray and Anyscale Make it Easy to do Massive-scale ML on Aerial Imagery

Tuesday, June 22, 8:45PM UTC

Richard Decal, Lead ML Engineer, Dendra Systems

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This talk outlines how Dendra Systems leverage Ray and Anyscale to parallelize their workloads across a cluster containing dozens of GPUs in a single Python script. Richard will discuss how Dendra optimized their inference pipelines to saturate their clusters' network I/O limits using Ray Serve.
Richard will then describe how Anyscale makes it easy to run this Ray application in production: running seamlessly in their BitBucket CI and also supporting a microservice to launch jobs programmatically.

Speakers

Richard Decal

Lead ML Engineer, Dendra Systems

Richard Decal is a machine learning scientist on a mission to fight against climate change. He is the Lead ML Engineer at Dendra Systems, where he is working on scaling ecosystem-restoring drones to the planetary scale.