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

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

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

The rise of generative AI has made one thing clear: text no longer needs to remain static. With its latest release, Speechify ...

In machine learning, self-supervised learning is a process in which the model instructs itself to learn a specific portion of the input from another portion of the input.

Vice President of AI & Quantum Computing, Paul Smith-Goodson gives his analysis of quantum machine learning models and IonQ's strategy to make it a reality.