Code Monkey home page Code Monkey logo

distributedai's Introduction

DistributedAI

This is the distributed AI project @ zju.

We will focus on the research of:

  1. Distributed Machine Learning
  2. Blockchain

Installation

Docker installation

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.

Install Docker

Go to the docker webpage and follow the instruction for your platform.

Download Image

Next you can download the docker image:

docker pull lzhou1110/distributed_ai_zju

Get Git Repository

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.

Change into directory

cd DistributedAI

Note: you need to be in the DistributedAI directory every time you want to run/update the book.

Run Notebook

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

Usage

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/

Contributing

  1. Fork it!
  2. Create your feature branch: git checkout -b my-new-feature
  3. Commit your changes: git commit -am 'Add some feature'
  4. Push to the branch: git push origin my-new-feature
  5. Submit a pull request :D

Mendeley Group

We also have a Mendeley group: mendeley.com/community/distributedaizju

History

The tensorflow mnist examples were from: https://github.com/ianlewis/tensorflow-examples

Credits

This project is led by (in alphabetic order):

License

Apache License 2.0

distributedai's People

Contributors

fallenk avatar itemzheng avatar lzhou1110 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.