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ray-summit-2022-training's Introduction

Welcome to Ray Summit 2022 Training

ยฉ 2019-2022, Anyscale. All Rights Reserved'

Welcome to the Ray Summit 2022 training tutorials on Ray, the system for scaling your Python and AI/ML applications from a laptop to a cluster.

Outline for the all the tutorial Lessons ๐Ÿ“–

Class Ray Components and Library Description
1 Ray Core Introduction to Ray for Distributed Applications
2 Ray Serve Machine Learning Model Deployment and Serving with Ray Serve
3 Ray RLlib Introduction to Reinforcement Learning and RLlib

IMPORTANT NOTE: Modules and materials in these tutorials have been tested with Ray release x.y and supported Python 3.7 and 3.8.

๐Ÿ‘ฉ Set up instructions for Anyscale

There is nothing you need to setup, as the Anyscale hosted environment will provide everything: all notebooks for each class, data files, and all relevant python packages will be installed on the cluster.

However, consider cloning or downloading a release of the tutorial notebooks and supporting software from the Ray Summit training repo, so you have a local copy of everything.

๐Ÿ‘ฉ Setup instructions for local laptop ๐Ÿ’ป

This is optional if you want to install training material on your laptop at home, after training is over.

Using conda

If you need to install Anaconda, follow the instructions here. If you already have Anaconda installed, consider running conda upgrade --all.

  1. conda create -n ray-summit-training python=3.8
  2. conda activate ray-summit-training
  3. git clone [email protected]:anyscale/ray-summit-2022-training.git
  4. cd to <cloned_dir>
  5. python3 -m pip install -r requirements.txt
  6. python3 -m ipykernel install
  7. jupyter lab

If you are using Apple M1 laptop ๐ŸŽ follow the following instructions:

  1. conda create -n ray-summit-training python=3.8
  2. conda activate ray-summit-training
  3. conda install grpcio
  4. git clone [email protected]:anyscale/ray-summit-2022-training.git
  5. cd to <cloned_dir>
  6. python3 -m pip install -r requirements.txt
  7. python3 -m ipykernel install
  8. conda install jupyterlab
  9. jupyter lab

Using only pip

  1. git clone [email protected]:anyscale/ray-summit-2022-training.git
  2. cd to <cloned_dir>
  3. python3 -m pip install -r requirements.txt
  4. python3 -m ipykernel install
  5. jupyter lab

Let's have ๐Ÿ˜œ fun @ Ray Summit 2022!

Thank you ๐Ÿ™

ray-summit-2022-training's People

Contributors

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