Description:
Rittman Mead's data science team recently collaborated with a higher education institution to create machine learning models that assess the likelihood of students failing to enroll at the start of term. The outcomes, presented through an interactive dashboard, enabled the admissions office to visualize and monitor these predictions dynamically, with the goals of:
- Increasing enrollment rates
- Reducing the number of individuals who failed to enroll
These principles can be applied not only to higher education institutions but also to other industries that rely on customer or client engagement.
Join the Oracle Analytics Product Marketing team along with partner, Rittman Mead, to explore this real-world use case combining machine learning models with interactive data visualizations.
Presented by:
- Hannah Patrick, Lead Data Scientist, Rittman Mead
- Jon Mead, Managing Director and Co-founder, Rittman Mead
- Barry Mostert, Senior Director, Product Marketing, Oracle AI and Analytics
- Nick Engelhardt, Senior Director, Product Marketing, Oracle AI and Analytics