Machine learning has emerged as a powerful tool in condensed matter physics, offering new perspectives on the exploration of quantum many-body systems, phase transitions and exotic states of matter.

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...