/
navbar.yml
53 lines (53 loc) · 1.71 KB
/
navbar.yml
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- file: ray-overview/getting-started
title: "Get Started"
- file: ray-overview/use-cases
title: "Use Cases"
- file: ray-overview/examples
title: "Example Gallery"
- file: ray-overview/installation
title: "Library"
sections:
- file: ray-core/walkthrough
title: Ray Core
caption: Scale general Python applications
- file: data/data
title: Ray Data
caption: Scale data ingest and preprocessing
- file: train/train
title: Ray Train
caption: Scale machine learning training
- file: tune/index
title: Ray Tune
caption: Scale hyperparameter tuning
- file: serve/index
title: Ray Serve
caption: Scale model serving
- file: rllib/index
title: Ray RLlib
caption: Scale reinforcement learning
- file: index
title: "Docs"
- link: https://discuss.ray.io
title: "Resources"
sections:
- link: https://discuss.ray.io
title: "Discussion Forum"
caption: Get your Ray questions answered
- link: https://github.com/ray-project/ray-educational-materials
title: "Training"
caption: Hands-on learning
- link: https://www.anyscale.com/blog
title: "Blog"
caption: Updates, best practices, user-stories
- link: https://www.anyscale.com/events
title: "Events"
caption: Webinars, meetups, office hours
- link: https://www.anyscale.com/blog/how-ray-and-anyscale-make-it-easy-to-do-massive-scale-machine-learning-on
title: "Success Stories"
caption: Real-world workload examples
- file: ray-overview/ray-libraries
title: "Ecosystem"
caption: Libraries integrated with Ray
- link: https://www.ray.io/community
title: "Community"
caption: Connect with us