For enterprise businesses, applying advanced machine learning (ML) techniques like deep learning can deliver transformative business outcomes, yet the black-box nature of these approaches creates barriers of understanding that can slow adoption to a halt. ML model interpretability, or the ability to explain why and how a model makes a prediction, can enable business stakeholders to quickly understand the how and why of predictive outcomes and confidently make decisions that optimize for future business results
JOIN THIS WEBINAR TO:
Discover best practices for building and deploying interpretable ML models at scale
Learn how Cloudera Machine Learning’s model ops and interactive applications functionalities deliver business-ready predictive apps for business users
Explore an in-depth technical guide to ML interpretability and working application prototypes from Cloudera Fast Forward Labs
