Hands-on Workshop - Improving AI Predictions using Location Data

Participate in a hands-on workshop exploring how to enhance AI predictions by incorporating location data using Oracle Autonomous Database's Spatial AI capabilities. Learn from Oracle experts Rahul Tasker, Denise Myrick, and Ramu Murakami Gutierrez as they demonstrate practical applications of spatial predictive analytics through Python APIs. Discover how location information can significantly impact business decisions by examining real-world scenarios such as predicting highway project safety impacts, identifying unemployment hotspots, and forecasting solar energy adoption in housing subdivisions based on neighbor influence patterns. Work directly with vehicle registration and demographic datasets to build enhanced machine learning models that better predict electric vehicle adoption rates. Master the fundamentals of location-based analysis and understand how spatial algorithms can improve ML performance by accounting for geographical variations, detecting spatial patterns, identifying geographical hotspots and outliers, and incorporating neighborhood effects into predictive models. Gain practical experience with Oracle Autonomous Database's spatial features while developing skills in location-driven machine learning techniques that can transform how you approach geographically-influenced business problems.