👉 Monte computing, or Monte Carlo methods, is a class of computational algorithms that rely on repeated random sampling to obtain numerical results. These methods are particularly useful for solving problems that involve uncertainty or randomness, such as simulations in physics, finance, and engineering. By generating a large number of random samples, Monte Carlo methods estimate the probability distribution of outcomes and can approximate complex integrals or solve differential equations that are difficult or impossible to handle analytically. The accuracy of Monte Carlo simulations improves with the number of samples, making them a powerful tool for modeling systems with inherent variability.
