RLlib on Ray is an industrial-strength reinforcement learning (RL) framework with the power of Ray autoscaling built in.
Get an overview of RLlib, and learn why organizations like Wildlife Studios and Dow Chemicals are using it to apply RL to business problems like recommendations and supply chain optimization.
This webinar will also show how to set up an environment, train a model, and deploy to an HTTPS endpoint to serve your policy in production.
Will is a Product Manager for ML at Anyscale. Previously, he was the first ML Engineer at Coinbase, and ran a couple of ML-related startups, one in the data labeling space and the other in the pharmaceutical space. He has a BS in CS and Music Composition from MIT, and did his master's thesis at MIT in machine learning systems. In his spare time, he produces electronic music, travels, and tries to find the best Ethiopian food in the Bay Area.
Sven is a machine learning engineer at Anyscale Inc. and the lead developer of RLlib, Ray's industry-leading, open-source reinforcement learning (RL) library. He is currently focusing his efforts on making offline RL algorithms a viable solution for many industry use cases, making attention nets the new go-to models for partially observable environments, designing new APIs and simplifying existing ones, as well as, asserting high levels of stability and test coverage to ensure RLlib's rapid adoption in industry and research. He is also actively helping to grow the community and contributor base around RLlib. Before starting at Anyscale, he has been a leading developer of other successful open-source RL library projects, such as "RLgraph" and "TensorForce".