Explore a 31-minute lecture on reinforcement learning applications in online Bayesian estimation for noise-driven coherent rotation of a spin qubit. Delivered by Jan Adrian Krzywda from the University of Leiden, this talk delves into advanced concepts at the intersection of quantum physics and machine learning. Gain insights into how reinforcement learning techniques can be applied to improve estimation processes in quantum systems, specifically focusing on spin qubits undergoing coherent rotation in the presence of noise. Understand the challenges and potential benefits of using online Bayesian methods in this context, and discover how these approaches can enhance our understanding and control of quantum systems.