demos

AutoML Streams Dockerized Demos

A collection of AutoML Streams demos than can be executed in Docker and can use Kafka as streaming data source.

Running instructions

Requirements

Required: Docker

Strongly recommended: Docker Compose, Make

Useful: kafkacat

Starting the containers

All containers at once:

make up

Individual containers:

docker-compose up auto-sklearn zookeeper broker

Publishing a dataset to Kafka

OpenML dataset:

To be added. For now see: https://github.com/AlexImb/automl-experiments

For any other dataset:

cat ./_datasets/covtype.csv | kafkacat -P -b localhost -t covtype   

Running an experiment

docker-compose exec h2o python training/h2o-pretrained.py

Opening Jupyter/JupyterLab

Find the right port for the experiment/service in the docker-compose.yml

Navigate to: localhost:<port>, for example: localhost:8887

Get the Jupyter token by running

docker-compose logs <service_name>

For example:

docker-compose logs auto-sklearn

Copy the token and use it to login in Jupyter.

Stopping the containers

All containers at once:

make down