Often, the final step in the machine learning solution deployment step goes unfinished: monitoring. Data monitoring helps ensure data integrity for your applications and dashboards by identifying data drift and gaining insight into data changes. Model monitoring helps identify changes in model accuracy which can result from, e.g., changes in customer behavior as well as upstream data quality. In this session, you'll learn how to detect issues early and take corrective action before these issues have a significant impact, explore the monitoring problem, where it fits in the ML process, and how to use no-code data and model monitoring user interfaces in Autonomous Database. Join us to learn about this key MLOps topic along with demonstrations. Presenter: Mark Hornick, Senior Director, Oracle Machine Learning and AI Product Management Date: Thursday, May 1, 2025 | 9:00am Pacific / 12:00pm Eastern Speaker(s): Mark Hornick, Agenda: https://us02web.zoom.us/webinar/register/4017283227834/WN_u_aGl58mS5C-qsWlUj0gQg#/registration Please register in above link and here, too. We appreciate that for the visibility of our talks. Virtual: https://events.vtools.ieee.org/m/483320

I will share here our experiences with our talks with Senators and Congresswomen Congressmen. Today's meeting date will be my 20th Year Anniversary with Oracle, too. we will celebrate together. Bldg: Dunkin, 239 Main Dunstable Rd., NASHUA, New Hampshire, United States, 03062