Monte Carlo Simulations
Monte Carlo simulations are a computational technique that uses random sampling and statistical modeling to estimate the probability of different outcomes in complex systems or processes. They are widely used to analyze risk, uncertainty, and variability in fields such as finance, engineering, and science. By running thousands or millions of simulations with random inputs, they provide insights into the likelihood of various scenarios.
Developers should learn Monte Carlo simulations when building applications that involve risk assessment, financial modeling, or optimization under uncertainty, such as in algorithmic trading, project management, or scientific research. They are particularly useful for problems where analytical solutions are difficult or impossible, allowing for probabilistic forecasting and decision-making in data-driven systems.