Math & Optimization · advanced · concept 50 of 176
Monte Carlo Methods
Answering hard questions by random sampling: estimate what you cannot compute by simulating it many times. The name behind MCMC in Bayesian inference, Monte Carlo returns in reinforcement learning, dropout-based uncertainty, and the tree search that powered AlphaGo. One idea, remarkable reach.
Key terms
Random samplingMCMCMonte Carlo Tree SearchSimulationVariance reduction
Learn these first
Where you meet it in the real world
AlphaGo's tree search, risk simulation in finance, Bayesian posterior sampling, uncertainty estimates
Videos
▶ 6. Monte Carlo Simulation ↗
MIT OpenCourseWare · YouTube
▶ What is Monte Carlo Simulation? ↗
IBM Technology · YouTube
Guides and articles
22.6. Random Variables — Dive into Deep Learning 1.0.3 documentation ↗
Dive into Deep Learning
Courses, papers, and more