The development of every field relies on a few foundational classic books, and artificial intelligence is no exception.

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

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

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 ...

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 ...

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data scientists should master both supervised ...

This issue has now been addressed. Li Hang's newly launched book 'Machine Learning Methods (2nd Edition)' dedicates a chapter ...