Recently, model-based reinforcement learning has been considered a crucial approach to applying reinforcement learning in the physical world, primarily due to its efficient utilization of samples.

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

The return to project-based learning, paired with today's AI tools, has created a new learning paradigm. Here, Mark Frydenberg, distinguished lecturer of Computer Information Systems and director of ...

See how AI and machine learning are transforming people search accuracy. Learn how ML improves precision and recall, powers ...

Corrected: This story has been updated to correct the number of districts participating in Washington state’s Mastery-Based Learning Collaborative. Every state now allows schools to embrace competency ...

Education experts are encouraging schools to consider problem-based learning (PBL) in a move to improve engagement and creativity among high school students. New research demonstrates how hands-on, ...