5 Get Started with Notebooks Classic for Data Analysis and Data Visualization

Oracle Machine Learning Notebooks Classic is based on Apache Zeppelin technology. You can write code, text, create visualizations, and perform data analytics including machine learning. Notebooks work with interpreters in the back-end. In Oracle Machine Learning, notebooks are available in a project, where you can create, edit, delete, and even save notebooks as templates.

Note:

OML Notebooks Classic has been deprecated since June 11, 2024. On October 29, 2024, you will no longer be able to create Classic notebooks, save them as templates, or select them for job scheduling. Existing Classic notebooks can be opened in read-only mode. You can continue to convert Classic notebooks to the new format using the Copy to OML Notebooks button on the Notebook Classic listing page.

On December 31, 2024, Classic notebooks will no longer be available. The ADMIN user can access Classic notebooks in read-only mode and convert them to the new format. Jobs that still use Classic notebooks will show a status of Disabled. Associated job logs will not be accessible.

On June 4, 2025, the ADMIN user will no longer have access to Classic notebooks, and any remaining notebooks will be deleted. If you have Classic notebooks or Classic template notebooks (personal or shared) that you wish to keep, you must convert these to the new format. If you have jobs that rely on Classic notebooks, these jobs must either be updated with a new notebook or recreated with a new notebook.

• Create a Notebook Classic
  A Notebook Classic is a web-based interface for data analysis, data discovery, data visualization and collaboration.
• Edit Your Notebook Classic
  Upon creating an OML Notebook Classic, it opens automatically, presenting you with a single paragraph using the default %sql interpreter. You can change the interpreter by explicitly specifying one of %script, %python, %sql , %r , %md or %conda.
• Export a Notebook
  You can export a Notebook in Native format (.dsnb) file, Zeppelin format ( .json ) file, in Jupyter format ( .ipynb ), and later import them in to the same or a different environment.
• Import a Notebook
  You can import notebooks across Pluggable Databases (PDBs) into your workspace. Oracle Machine Learning UI supports the import of notebooks in the native format (.dsnb), Zeppelin (.json) and Jupyter (.ipynb) notebooks.
• Version a Notebook Classic
  You can version or create a backup of a Notebook Classic, experiment on it, and revert to the original notebook, if required.
• Create Check Box Forms in Notebooks
  The Check Box Form supports multiple selection of inputs in a paragraph. The inputs are available as check box options in the notebook.
• Create Select Forms in Notebooks
  The Select Form allows you to select input values from a list of values, and dynamically retrieve the selected values as defined in the paragraph.
• Create Text Input Forms in Notebooks
  The Text Input form allows you to dynamically retrieve values as defined in the notebook.
• Collaborate in Oracle Machine Learning
  Two or more users can collaborate and share Oracle Machine Learning User Interface (UI) notebooks with other users.