Skip to content

Experimenting with the ray project - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

adipolak/play-with-ray

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 

Repository files navigation

play-with-ray

Experimenting with the ray project - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

To give it a try:

clone the repo, cd and run:

docker run -it --memory="28g" --memory-swap="30g"  -p 8888:8888 --mount type=bind,source=$(pwd),target=/home/jovyan adipolak/ml-with-apache-spark

This repo is based on the Ray quickstart guide.

About

Experimenting with the ray project - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published