This is the distributed AI project @ zju.
We will focus on the research of:
- Distributed Machine Learning
- Blockchain
We assume you have a command line interface (CLI) in your OS
(bash, zsh, cygwin, git-bash, power-shell etc.). We assume this CLI sets
the variable $(pwd) to the current directory. If it doesn't replace
all mentions of $(pwd) with the current directory you are in.
Go to the docker webpage and follow the instruction for your platform.
Next you can download the docker image:
docker pull lzhou1110/distributed_ai_zju
You can use the git installation in the docker container to get the repository:
docker run -v "$(pwd)":/home/zju/work lzhou1110/distributed_ai_zju git clone https://github.com/lzhou1110/DistributedAI.git
Note: this will create a new DistributedAI directory in your current directory.
cd DistributedAI
Note: you need to be in the DistributedAI directory every time you want to run/update the book.
docker run -it --rm -p 8888:8888 -v "$(pwd)":/home/zju/work lzhou1110/distributed_ai_zju
You are now ready to visit the jupyter notebook at http://localhost:8888
Once installed you can always run your notebook server by first changing
into your local DistributedAI directory, and then executing:
docker run -it --rm -p 8888:8888 -v "$(pwd)":/home/zju/work lzhou1110/distributed_ai_zju
This is assuming that your docker daemon is running and that you are
in the DistributedAI directory. How to run the docker daemon
depends on your system.
For markdown tutorial, refer to: https://guides.github.com/features/mastering-markdown/
- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request :D
We also have a Mendeley group: mendeley.com/community/distributedaizju
The tensorflow mnist examples were from: https://github.com/ianlewis/tensorflow-examples
This project is led by (in alphabetic order):
- Chao Wu @wuchaozju
- Jun Xiao junx@cs.zju.edu.cn
Apache License 2.0