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<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MC Simulation - Home</title>
<link rel="icon" type="image/png" href="./Website-image/favicon.png">
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<div class="header-container">
<h1>Monte-Carlo simulation in Python</h1>
</br>
<a href="https://arunp77.github.io/MonteCarlo-simulation/">
<img src="Website-image/MCS.png" alt="Your Image" class="profile-image">
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<li><a href="index.html">Home</a></li>
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<a href="https://arunp77.github.io/">My webpage</a>
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<section id="home">
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<h2>Welcome to My Website</h2>
</section>
<h2>Monte Carlo simulations and Machine learning algorithms</h2>
<ul>
<li>Monte Carlo simulations are a class of computational techniques that use random sampling to approximate and analyze complex systems or problems.</li>
<li>While Monte Carlo simulations themselves are not typically considered machine learning algorithms, they can be combined with machine learning techniques to enhance their capabilities.</li>
<li>It's important to note that the specific choice of machine learning algorithms in Monte Carlo simulations depends on the nature of the problem, the available data, and the objectives of the simulation.</li>
<li>Different algorithms may be more suitable for different scenarios, and their selection should be based on careful analysis and experimentation.</li>
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© 2023 <a href="https://sites.google.com/view/aruncosmo/home" target="_blank">Arun Kumar Pandey</a>. All rights reserved.
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