Tag: interpretability

Analytics
Leo Sadovy 0
Opportunities for analytics: Interpretation

Where in your business process can analytics and AI play a contributing role in enhancing your decision making capability?  At the information interpretation stage.  As a framework for understanding where analytic and AI opportunities may arise, the simple diagram below illustrates the relationships between data, information and knowledge, and how

Advanced Analytics | Machine Learning
Wayne Thompson 0
Why you should add statistical learning to your machine learning tool kit

Data scientists naturally use a lot of machine learning algorithms, which work well for detecting patterns, automating simple tasks, generalizing responses and other data heavy tasks. As a subfield of computer science, machine learning evolved from the study of pattern recognition and computational learning theory in artificial intelligence. Over time, machine learning has borrowed from many

Advanced Analytics | Analytics | Artificial Intelligence | SAS Events
Oliver Schabenberger 0
Meet 5 data pioneers developing AI solutions for the real world

Everyone is talking about artificial intelligence. Unfortunately, a lot of what you hear about AI in the movies and on the TV is sensationalized for entertainment. Indeed, AI is overhyped. But AI is also real and powerful. Consider this: engineers worked for years on hand-crafted models for object detection, facial

Artificial Intelligence
Leo Sadovy 0
AI and trust

Andy Dufresne, the wrongly convicted character in The Shawshank Redemption, provocatively asks the prison guard early in the film: “Do you trust your wife?” It’s a dead serious question regarding avoiding taxes on a recent financial windfall that had come the guard's way, and leads to events that eventually win

Advanced Analytics | Artificial Intelligence | Machine Learning
Ilknur Kaynar Kabul 0
Interpretability is crucial for trusting AI and machine learning

As machine learning takes its place in many recent advances in science and technology, the interpretability of machine learning models grows in importance. We are surrounded with applications powered by machine learning, and we’re personally affected by the decisions made by machines more and more every day. From the mundane