What are the different templates available in Oracle Machine Learning?

In Oracle Machine Learning, the availability of different template types enhances the user experience by providing structured pathways for various machine learning tasks. Shared templates allow users to access predefined machine learning configurations that can be utilized across different projects and by different users within the organization. This promotes collaboration and facilitates the sharing of best practices among data scientists and machine learning practitioners.

Shared templates typically encompass a variety of machine learning workflows, providing a solid foundation for creating models efficiently. Users can build upon these templates, adapting them to their specific needs while benefiting from standardization and the collective insights embedded within them.

The other categories do not exist in the context described. Personal templates would imply individualized settings that are not available for collaboration. Example templates may not be a formal category in the system, and fixed templates would suggest a static collection that lacks the nuance of shared collaboration. Thus, the correct option highlights the collaborative and flexible nature of machine learning procedures in Oracle Machine Learning.