Concepts and algorithms of machine learning including version-spaces, decision trees, instance-based learning, networks, evolutionary computation, Bayesian learning and reinforcement learning.

Humans intuitively understand causality, but AI struggles. Researchers look at creating AI systems that can learn causal representations.

Blake Miller, Fridolin Linder, Walter R. Mebane Jr. Supervised machine learning methods are increasingly employed in political science. Such models require costly manual labeling of documents. In this ...

MIT's AI-infused mechanical engineering class, led by Professor Faez Ahmed, gains popularity for its innovative design ...

This blog is the latest in the AI Leadership Brain Trust series which defines 50 key competencies required to build a world-class AI center of excellence in a large enterprise. This blog defines ...

David H. Jonassen, On the Role of Concepts in Learning and Instructional Design, Educational Technology Research and Development, Vol. 54, No. 2 (Apr., 2006), pp. 177-196 ...