Reinforcement learning is a type of machine learning that assigns positive or negative values to certain outcomes.

Professor Li Hang's new book is positioned as a university textbook and a reference for professionals, suitable for readers with a certain background in calculus, linear algebra, and computer science.

The near-term feasibility of self-driving cars depends on the limits of current machine learning approaches. This article is about using reinforcement learning to solve path planning and driving ...

Some tasks, like the language modeling performed by systems like GPT-4, use clever combinations of supervised and unsupervised techniques known as self- and semi-supervised learning. Finally, ...

“Successful machine learning is only as good as the data available, which is why it needs new, updated data to provide the most accurate outputs or predictions for any given need,” said ...