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:
which will prompt a username and password.
At any time to view which account you're logged in with, you can use:
You can also logout via:
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:
In order to clear the cached information about all the previous users, do:
If you have forgotten your password, and would like to reset it, do: