Learn Interpretability for Data Science
Editor’s note: Rajiv Shaw will be a speaker at ODSC East 2019 this May! Be sure to check out his talk, “Deciphering the Black Box: Latest Tools and Techniques for Interpretability” there. The impact of machine learning has been tremendous, whether it’s measured in dollars (trillions) or human impact... Read more
Explainable AI: From Prediction To Understanding
It’s not enough to make predictions. Sometimes, you need to generate a deep understanding. Just because you model something doesn’t mean you really know how it works. In classical machine learning, the algorithm spits out predictions, but in some cases, this isn’t good enough. Dr. George Cevora explains why... Read more
The Importance of Explainable AI
AI algorithms can be trained to perform many disparate tasks, but these systems often are opaque and operate in a black box, meaning users don’t always know how decisions are being made. AI-powered systems, frequently using deep learning methods, can be given extraordinarily complex tasks and can make great... Read more