Robust

: your code works but confidence is low, so that you hesitate to the touch it. Adding a feature means performing open-heart surgery on the appliance, modifying existing business logic reasonably than extending the...

Explainability in AI is important for gaining trust in model predictions and is extremely essential for improving model robustness. Good explainability often acts as a debugging tool, revealing flaws within the model training process....

was co-authored by Sebastian Humberg and Morris Stallmann. Introduction      Machine learning (ML) models are designed to make accurate predictions based on patterns in historical data. But what if these patterns change overnight? For...

Never miss a brand new edition of , our weekly newsletter featuring a top-notch choice of editors’ picks, deep dives, community news, and more. Many practitioners wish to jump headfirst into the nitty-gritty details of...

AI growth and advancements have been exponential over the past few years. Statista reports that by 2024, the worldwide AI market will generate a staggering revenue of around $3000 billion, in comparison with $126...