Machine Learning

This document gives an overview of the characteristics and machine learning features.

Machine learning features of commercetools Composable Commerce provide automated predictions by autonomously learning from data. In general, these features make use of artificial intelligence to reduce the amount of manual work that is required to manage projects. For example, machine learning can be used to automatically predict which of potentially thousands of available categories fit best to a given product.

Since the machine learning features are in an early stage of development, your feedback can have a large impact. If there is anything you would like to tell us (positive experiences, criticism, or requests for new features), please contact our support.

Currently, the following machine learning features are available:

Difference from other endpoints

Compared to other endpoints of commercetools Composable Commerce APIs, machine learning features have some characteristic differences:

The results are based on probabilities and have a margin of error, which is indicated by confidence scores in the responses (0.0 is low, 1.0 is high).
The response times are typically longer since the underlying computations can be complex.

Hosts

The Machine Learning API has different hosts from the HTTP API. The Machine Learning API is hosted at the following URLs:

Region	API URL
North America (Google Cloud, Iowa)	`https://ml-us.europe-west1.gcp.commercetools.com/`
Europe (Google Cloud, Belgium)	`https://ml-eu.europe-west1.gcp.commercetools.com/`

If documentation refers to https://ml-{mlRegion}.europe-west1.gcp.commercetools.com/, the {mlRegion} placeholder has to be replaced with us or eu respectively.

The Machine Learning APIs are available in the Google Cloud Regions in Europe and North America.

Confidence filtering

Queries for a collection of predictions can optionally provide confidence bounds on the returned predictions. This allows users to specify that the endpoint should only return those predictions about which we are more confident than confidenceMin and less confident than confidenceMax.