ray/doc/source/_toc.yml
Max Pumperla 4dd221f848
[Docs] Ray Data docs target state (#21931)
Preview: [docs](https://ray--21931.org.readthedocs.build/en/21931/data/dataset.html)

The Ray Data project's docs now have a clearer structure and have partly been rewritten/modified. In particular we have

- [x] A Getting Started Guide
- [x] An explicit User / How-To Guide
- [x] A dedicated Key Concepts page
- [x] A consistent naming convention in `Ray Data` whenever is is referred to the project.

This surfaces quite clearly that, apart from the "Getting Started" sections, we really only have one real example. Once we have more, we can create an "Example" section like many other sub-projects have. This will be addressed in https://github.com/ray-project/ray/issues/21838.
2022-01-27 13:14:36 -08:00

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format: jb-book
root: index
parts:
- caption: Overview
chapters:
- file: ray-overview/index
- file: ray-overview/installation
- file: ray-overview/learn-more
- file: ray-overview/ray-libraries
- caption: Ray ML | Machine Learning
chapters:
- file: data/dataset
title: Ray Data
sections:
- file: data/getting-started
- file: data/user-guide
- file: data/key-concepts
- file: data/examples/big_data_ingestion
- file: train/train
title: Ray Train
sections:
- file: train/user_guide
- file: train/examples
- file: train/architecture
- file: train/migration-guide
- file: raysgd/raysgd
title: "RaySGD v1: Distributed Training Wrappers"
- file: tune/index
title: Ray Tune
sections:
- file: tune/key-concepts
- file: tune/user-guide
- file: tune/tutorials/overview
sections:
- file: tune/tutorials/tune-tutorial.rst
- file: tune/tutorials/tune-advanced-tutorial.rst
- file: tune/tutorials/tune-distributed.rst
- file: tune/tutorials/tune-lifecycle.rst
- file: tune/tutorials/tune-mlflow.rst
- file: tune/tutorials/tune-pytorch-cifar.rst
- file: tune/tutorials/tune-pytorch-lightning.rst
- file: tune/tutorials/tune-serve-integration-mnist.rst
- file: tune/tutorials/tune-sklearn.rst
- file: tune/tutorials/tune-xgboost.rst
- file: tune/tutorials/tune-wandb.rst
- file: tune/examples/index
- file: tune/contrib
- file: serve/index
title: Ray Serve
sections:
- file: serve/end_to_end_tutorial.rst
- file: serve/core-apis
- file: serve/http-servehandle
- file: serve/deployment
- file: serve/ml-models
- file: serve/pipeline
- file: serve/performance
- file: serve/architecture
- file: serve/tutorials/index
- file: serve/faq
- file: rllib/index
title: Ray RLlib
sections:
- file: rllib/rllib-toc
- file: rllib/core-concepts
- file: rllib/rllib-training
- file: rllib/rllib-env
- file: rllib/rllib-models
- file: rllib/rllib-algorithms
- file: rllib/rllib-sample-collection
- file: rllib/rllib-offline
- file: rllib/rllib-concepts
- file: rllib/rllib-examples
- file: rllib/rllib-dev
- file: workflows/concepts
title: Ray Workflows
sections:
- file: workflows/basics
- file: workflows/management
- file: workflows/actors
- file: workflows/metadata
- file: workflows/events
- file: workflows/comparison
- file: workflows/advanced
- file: ray-more-libs/index
title: More Ray ML Libraries
- caption: Ray Core | Distributed Applications
chapters:
- file: ray-core/walkthrough
title: Getting Started
- file: ray-core/using-ray
title: "User Guide"
- file: ray-core/examples/overview
title: "Tutorials and Examples"
- caption: Ray Clusters | Deployments
chapters:
- file: cluster/quickstart
- file: cluster/user-guide
- file: cluster/cloud
- file: cluster/deploy
- caption: References
chapters:
- file: ray-references/api
- file: ray-references/faq
- caption: Developer Guides
chapters:
- file: ray-contribute/getting-involved
sections:
- file: ray-contribute/development
- file: ray-contribute/fake-autoscaler
- file: ray-core/configure
- file: ray-observability/index
- file: ray-design-patterns/index
- file: ray-contribute/whitepaper
# TODO: Add examples section