The Future of Prediction: Unsupervised Learning

Advances in AI in recent years have focused on the ability to build better predictive models using a variety of techniques, not the least of which is deep learning. These approaches, however, require massive datasets and restrict their utility for enterprise grade problems. The future of prediction lies upstream in the analytical process – in the unsupervised learning techniques of segmentation, anomaly detection and hotspot detection. Jennifer will dive deeper into unsupervised learning and why this is the next frontier in AI. She’ll break the problem down technically and practically – discussing feature generation, dimensionality reduction and how to get started. In doing so, she’ll explore key enterprise uses cases ranging from fraud detection, financial crime and population health.