Monte Carlo methods

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An Overview of Monte Carlo Methods

Towards Data Science

Monte Carlo (MC) methods are a subset of computational algorithms that use the process of repeated random sampling to make numerical estimations of unknown parameters. They allow for the modeling of…

A Gentle Introduction to Monte Carlo Methods

Towards Data Science

Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept behind these methods is the use of…

Towards Data Science

Introduction Once again we’re off to the casino, and this time it’s situated in sunny Monte Carlo, made famous by its appearance in the classic movie Madagascar 3: Europe’s Most Wanted (although there...

Monte Carlo Methods and Simulations explained in real-life: modeling insomnia

Towards Data Science

Monte Carlo Methods is a group of algorithms that simulate the behavior of a complex system, or probabilistic phenomena, using inferential statistics.

Monte Carlo Methods Decoded

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The Basics Imagine you have a big, mysterious jar full of different-colored marbles. There is one problem: you can’t see inside it to count how many of each color there are. You want to know which col...

Just Keep Guessing: The Power of the Monte Carlo Method

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The Monte Carlo method is an incredibly powerful tool used in a wide variety of fields. From mathematics to science to finance, the Monte Carlo method can be used to solve a variety of unique and…

Gacha Simulation using Monte Carlo Method in R

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Monte Carlo Simulation Method is one of the most popular methods in simulation theory that relies on repeated random sampling to obtain desired numerical results. There is much application of this…

Monte Carlo Method Explained

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In this post, I will introduce, explain and implement the Monte Carlo method to you. This method of simulation is one of my favourites because of its simplicity and yet it’s a refined method to…

Probability Learning: Monte Carlo Methods

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Hello again friends! Welcome to Probability Learning! In this post we will see what Monte Carlo methods are, their different use cases, and how they are applied in the real world. Lets get to it! You…...

Monte Carlo Methods for Solving Reinforcement Learning Problems

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Due to not using a model, MC methods are unbiased. They are conceptually simple and easy to understand, but exhibit a high variance and cannot be solved in iterative fashion (bootstrapping). As mentio...

Monte Carlo Simulation in 3 Minutes

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Monte Carlo simulations are a computational method used to assign probabilities to events that would otherwise be difficult or impossible to mathematically calculate. Since these simulations involve…

Monte Carlo Without the Math

Towards Data Science

Monte Carlo simulations are extremely common methods in the world of data science and analytics. They can be used for everything from business process optimization to physics simulation…