Pass 1z0-1096-23 Exam Guide

• To segment your customer data for marketing research purposes and identify homogeneous groups to build supervised models, you should use clustering12.
• Clustering is a type of unsupervised machine learning that groups data points based on their similarities in terms of features or attributes. Clustering can help discover the underlying structure of the data and reveal the natural segments or categories within it12.
• Clustering can be useful for marketing research because it can help identify different types of customers based on their demographics, preferences, behaviors, or needs. Clustering can also help create customer profiles or personas that can be used to target specific segments with tailored marketing campaigns or offers12.
• Clustering can also be used as a preliminary step for building supervised models, such as classification or regression. By using the cluster labels as an additional feature or a target variable, supervised models can learn from the cluster information and improve their accuracy or performance12.

Explanation

https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/notebooks.html

Explanation

https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/notebooks-templates.html

Explanation

https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/create-notebooks-oml.html#GUID-0F489564-A628-478E-9898-1F94B0441026