Tabs for a DSL Project
A DSL project utilizes tabs to structure a data science experiment, enabling the outcome to be readily consumed for further data analytics.
Last updated
A DSL project utilizes tabs to structure a data science experiment, enabling the outcome to be readily consumed for further data analytics.
Last updated
The users can click on the View icon available for a DSL Project, it redirects to a page displaying the various tabs for the selected DSL Project.
Navigate to the Projects page.
Select a DSL project from the list.
Click the View icon.
The next page appears with the accessible tabs for the selected Project.
If you select a PySpark project, the following tabs will be available:
The following table provides an outlook of the various tabs provided to a DSL Project:
The Workspace tab inside a Repo Sync Project works like a placeholder to keep all the Git Hub & Git Lab Repository documents (folders and files) of the logged-in user.
The Data section focuses on how to add or upload data to your DSL Projects. This tab lists all the added Datasets, Data Stores, and Feature Stores for a Project.
The Model tab includes various models created, saved, or imported using the Data Science Lab module. It broadly lists Data Science Models, Imported Models, and Auto ML models.
The Auto ML tab allows the users to create various experiments on top of their datasets and list all their created experiments.
Please Note: The allocation of tabs to a DSL project is environment-based.
If the user selects the PySpark environment, the available tabs to the user will be Workspace and Data. The user will not have access to the Models and AutoML tabs.
The DSL Projects created based on Python or TensorFlow environments will contain all four tabs.
