A workflow defines how your model will be trained -

Typically, this will require hundreds lines of machine learning codes. On Datature's platform, however, workflows are built visually, without any codes, using our graphical user interface. We will then transpile the visual workflow into working and bug-free codes for you. To see how this fits into our overall work pipeline, look at Datature Pipeline.

Workflow Process

The process is simple -

Create a new workflow
Build a workflow
By dragging and dropping some building blocks, which we refer to as modules, on the workflow canvas, to define the settings for your Dataset Split, Data Augmentations, and Model Selection.
Preview your augmentations
If you have added an Augmentations Module to your workflow.
Run the workflow

Common Questions

Can I change my workflows after I've started running the workflow?

No, changing the workflow after the the run has been started will not affect the run. You can monitor training process and then delete the training even if it is ongoing.

Can I have multiple workflows?

You can have multiple workflows but only one workflow on each canvas. Having multiple workflows can help with experimentation and version control, as well as simultaneous testing of different setups. Simply create a new workflow for each of your experimentation and version control.

I am unable to run my workflow, what might be the issue?

Check for error messages. Make sure the modules are connected to each other, the workflow cannot be run if there are 'floating' modules on the canvas. Contact Us if you require support on getting your workflow to run.