Operations for an .ipynb File

This section aims at describing the various operations for a Data Science Notebook available under the TensorFlow or PyTorch environment.

A Data Science Notebook created under the PyTorch or TensorFlow environment will contain the following operations:

• ​Datasets: Add datasets and get a list of all the added datasets.

• ​Secrets: You can generate Environment Variables to save your confidential information from getting exposed.

• ​Algorithms: You can get steps on how to do Algorithm Settings and Project-level access to use Algorithms inside Notebook.

• ​Transforms: Save and load models with transform script, register them, or publish them as an API through the DS Lab module.

• ​Models: You can train, save, and load the models (Sklearn, Keras/TensorFlow, PyTorch). You can also register a model using this tab.

• Files: Create/ Upload data folders or files into the dedicated Data Sandbox location.

• ​Variable Explorer: Get detailed information on Variables declared inside a Notebook.

• Writers: Write the output of the DSL experiments into the supported range of the database writers.

• ​Find and Replace: You can search for a specific text inside your code and replace it if needed.

Please Note: Refer to the Data Science Lab Quick Start Flow page to get an overview of the Data Science Lab module in a nutshell.