Core Concepts


The Core Engine lets you build and execute Deep Learning pipelines. Pipelines are simply a sequence of data processing steps to train, evaluate and serve machine learning models.

Similar experiments should be grouped in the same workspace. In the same workspace, subsequent pipeline runs enable the Core Engine to skip certain processing steps - this caching is built-in natively and supported across all plans and for all types of datasets.

The usage of these pipelines is enabled by a configuration file. This is a YAML file and it includes all the possible configuration settings of a pipeline run. They define your features and labels, how your data is split and which preprocessing steps should be used, they configure your model and training (trainer), define the evaluator and contain optionally additional configuration for timeseries datasets.

For the Beta, an interaction with the Core Engine is only possible through o Command Line Interface (CLI). The remaining section of the documentation focuses on how to use this interface.


In order to use the Core Engine, you first need to first create an account here

You can login through:

cengine auth login

which will prompt a username and password.

At any time to view which account you're logged in with, you can use:

cengine auth whoami

You can also logout via:

cengine auth logout

Once logged-in, in order to create it easier to use interface, cengine caches the information about the active user.

In order to reset the cached information about only the specific user, do:

cengine auth reset

In order to clear the cached information about all the previous users, do:

cengine auth reset --all

If you have forgotten your password, and would like to reset it, do:

cengine auth resetpassword