GCP ML Node#

The GCP (Google Cloud Platform) ML Node allows a workflow to send data to Google ML and store the resulting predictions on the workflow payload.

GCP ML Node

Prerequisites#

If you're new to Google ML, TensorFlow, or machine learning in general, you may want to take some time to look through the following resources:

Configuration#

Configuration for the node is broken up into four sections.

Service Account Auth Token#

A service account auth token is required for the workflow to authenticate with Google ML. You may enter this token one of two ways:

Cloud ML Model Configuration#

Specify the name of the model for which you want to get predictions. You may optionally specify the model version as well; if no version is provided the model's default version will be used. Before you can get predictions from a model, you'll first need to train it with sample data and then deploy it.

Input#

The instances path is a payload path that points to the data you want to get predictions for.

Output#

The output path is a payload path at which to place the prediction results.