Explore Monte Carlo methods in this comprehensive 2-hour and 26-minute lecture from the Nordic Probabilistic AI School (ProbAI) 2024. Delve into the intricacies of these powerful computational algorithms as presented by Charles Margoissan. Gain insights into the application of Monte Carlo techniques in probabilistic artificial intelligence and machine learning. Access accompanying materials on GitHub to enhance your understanding and practical implementation skills. The lecture features professional editing by David Baumgartner and includes piano sound effects for an engaging learning experience. Whether you're a student, researcher, or practitioner in the field of AI and probability, this in-depth presentation offers valuable knowledge on Monte Carlo methods and their significance in modern computational approaches.
Overview
Syllabus
Monte Carlo Methods by Charles Margoissan
Taught by
Probabilistic AI School
