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HEAR FROM LEADERS DEVELOPING THE NEXT GENERATION OF AI APPLICATIONS USING RAY
LinkedIn’s AI Innovations: From Recommendations to Generative Innovations
AI/ML at Uber from Predictive to Generative Models
How Ray Transformed Niantic's Big Data Dilemma
Learn about Ray’s rich set of libraries and integrations
Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray.
Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms.
Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework.
Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO.
General Python apps
Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core.
Scale data loading, writing, conversions, and transformations in Python with Ray Datasets.
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O'Reilly Learning Ray Book
Get your free copy of Learning Ray, the first and only comprehensive book on Ray and its ecosystem, authored by members on the Ray engineering team
Supercharge your Ray journey with Anyscale
Anyscale is a managed cloud offering — from the creators of the Ray project — to create, run and manage your Ray workload. If you or your organization prefers the speed and convenience of a managed service over self-managing clusters and the infra they live on, this might be for you.