nginyc / rafiki

Rafiki is a distributed system that supports training and deployment of machine learning models using AutoML, built with ease-of-use in mind.

Rafiki

Rafiki is a distributed system that trains machine learning (ML) models and deploys trained models, built with ease-of-use in mind. To do so, it leverages on automated machine learning (AutoML).

Read Rafiki's full documentation at https://nginyc.github.io/rafiki/docs/latest

Quick Setup

Prerequisites: MacOS or Linux environment

1. Install Docker 18 (Ubuntu, MacOS) and, if required, add your user to docker group (Linux)

2. Install Python 3.6 (Ubuntu, MacOS)

3. Clone this project (e.g. with Git)

4. Setup Rafiki's complete stack with the setup script:

   bash scripts/start.sh

To completely destroy Rafiki's stack:

bash scripts/stop.sh

More instructions are available in Rafiki's Developer Guide.

Issues

Report any issues at Apache SINGA's JIRA or Rafiki's Github Issues

Acknowledgements

The research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its National Cybersecurity R&D Programme (Grant No. NRF2016NCR-NCR002-020), National Natural Science Foundation of China (No. 61832001), National Key Research and Development Program of China (No. 2017YFB1201001), China Thousand Talents Program for Young Professionals (3070011 181811).