With an Autonomous Database and Machine Learning capabilities in the database, it will be easier for data science teams and application developers to manage and deploy machine learning models. We are focusing on customer insurance data for a business selling insurance. The data contains over 15,000 customer information records and the insurance business wants to predict whether new customers will buy the insurance and whether customers have a high lifetime value (LTV). We can make predictions with machine learning.

In this session, we will start from zero and build an environment with machine learning models. We will create an Autonomous Database in the Cloud, load data, and connect to the Machine Learning environment. Using the sample data, we will train machine learning models and make predictions using SQL.

Agenda

• Machine Learning concepts.
• Oracle Machine Learning.
• Autonomous Database tools for Machine Learning.
• AutoML UI to create machine-learning models.

Speaker: Andrei Manoliu - Principal Product Manager, part of the Product Management Database Platform Technology Solutions team, helping partners and customers understand more about the Oracle Database in Oracle Cloud Infrastructure. 

Andrei started working with the Oracle Database at 9i first as a developer, learning Oracle Forms and Reports on the way. Later, he changed the role to a DBA managing 9i, 10g, 11g, and 12c databases. Taking a step forward in his journey, he was in a presales position and later a post-sales position, which got him closer to the Oracle Cloud and the Oracle Database Services in the cloud. Currently, he is part of the Product Management Database Platform Technology Solutions team, helping partners and customers understand more about the Oracle Database in Oracle Cloud Infrastructure.