Data visualization techniques for representing high-degree interactions and nuanced data structures. Contemporary linear model variants that incorporate machine learning and are appropriate for use in ...
The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...
Opinion
Archaic Methods in a Data Rich World: Why Educational Research Must Embrace AI Research Methods ()
AI in Education, Machine Learning, Educational Research Methods, Causal Inference, Explainable AI Mgonja, T. (2025) Archaic Methods in a Data Rich World: Why Educational Research Must Embrace AI ...
The applied mathematician and Ramsey Theory Group founder launches a mission to reshape how organizations understand and trust AI.
Machine learning is increasingly recognized as a pivotal tool in the evolution of cardiovascular medicine, promising to ...
Rachel is a Product Manager in Appen’s Autonomous Vehicles working group. In that role, she is working to provide high quality data on all levels of autonomy for motor vehicle clients. Prior to ...
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