Wallaroo Quick Start Examples
The following examples are made to work with Wallaroo. These demonstrate how to create work spaces, upload ML models, create and deploy pipelines. Each example contains a Jupyter notebook, the ML model, and sample data.
The easiest way to run these tutorials is through the following:
- Install Wallaroo into a Kubernetes cluster environment, and enable the Jupyter Hub service.
- Download this repository by either cloning the repo or downloading the .ZIP file from the release list.
- Copy this repo into your Jupyter Hub service. The easiest way is to upload a .ZIP file of this repository, then use the command line tools to unzip it.
A free community edition of Wallaroo is available from the Wallaroo Community Portal.
From there each directory contains a self-contained guide to help you understand how to use Wallaroo to deploy pipelines of models and manage the inputs and the outputs.
See the releases for individual .zip files for each tutorial.