No data prep, no feature engineering: Predictive modeling in 2025

Explore how innovative AI models are transforming traditional machine learning by simplifying workflows and delivering accurate predictions with up to 20x less effort. These cutting-edge models eliminate the need for data preparation, feature engineering, and training set generation. Instead, they leverage advanced techniques like Relational Deep Learning, Transformers, and Graph Neural Networks to train directly on your data warehouse.
Led by Stanford professor and Kumo AI Co-founder Jure Leskovec, this session dives into the mechanics of these models, their advantages over traditional ML methods, and their impact on various business operations. Watch an end-to-end example showcasing real-world applications and see how you can harness this technology to drive results.
Request a demo: kumo.ai/apply/