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A platform to automate the training (including hyper-parameter tuning) and inference of machine learning models

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SINGA-AUTO

SINGA-AUTO 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 SINGA-AUTO'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 SINGA-AUTO's complete stack with the setup script:

    if use docker swarm mode, use this script:

    bash scripts/docker_swarm/start.sh

    if use kubernetes mode, use this script:

    bash scripts/kubernetes/start.sh

To completely destroy SINGA-AUTO's stack:

if use docker swarm mode, use this script:

```sh
bash scripts/docker_swarm/stop.sh
```

if user kubernetes mode, use this script:

```sh
bash scripts/kubernetes/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).

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A platform to automate the training (including hyper-parameter tuning) and inference of machine learning models

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