Making ML Scaling a Simple Experience for Every Developer

Wednesday, November 2, 4:00PM UTC

Watch this on-demand webinar to learn how to make scaling ML and Python workloads a simple integrated experience. Watch the new Workspace Environment, powered by Ray, that makes it a simple developer experience to:

  • Easily Scale any AI/ML and Python workloads without any complex infrastructure or scaling complexity
  • Move and operationalize workloads to production without having to refactor any machine learning code
  • Unify the deployment and scaling experience without having to stitch together many different AI/ML tools and frameworks
  • Scale any workload, even on large data, without consuming too much costly compute

Hear and see how you can:

  • Develop and iterate scalable ML & Python workloads

  • Move machine learning workloads faster from development to production

  • Use the tools you know and love, without having to learn something new

  • Free yourself from stitching together many disparate tools and frameworks

  • Better than notebooks! Native support for git, yscode, your own IDEs

“Anyscale Workspaces allows me to go from development, to experimenting at scale, all the way to production within the same environment. Workspaces reduced context switching for us by 50% and integrates with other tools we use.” 

— Data Scientist, Manufacturing Conglomerate

“In the same time that it took to run our original workload (7 days), we were able to effortlessly migrate over our Python code to Anyscale, fine tune our job for scaling, and move to production effortlessly.”

Director Data, ML, and Technology, Biolexis Therapeutics