Machine Learning Everywhere

Wednesday, February 6
11:50 AM - 12:30 PM
Room 103

Data science is the critical element in exploiting data, but several problems prevent organisations from maximising its value. Data scientists often find it hard to work efficiently, with delays in getting access to needed data and resources. Enterprise developers find it hard to incorporate machine learning models into their applications, and IT spends too much time supporting complex environments. Business users rarely are directly involved in the process and don’t have the means to build and consume their own predictive models. All of this means that business executives are not seeing the full ROI they expect from their data science and analytics investments. In this session, we will introduce some cloud based solutions designed to address these challenges.


Stephen Weingartner
Solution Engineer
Stephen Weingartner has been with Oracle for 6 years as an Solution Engineer. His specialty is cloud based analytics and that extends into information management, big data, and machine learning. Prior to working at Oracle, Stephen had about 15 years’ experience in analytics / information management in the roles architecture, strategy, design, development, project management, and systems management.