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# Introduction
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This jupyter-book provides python implementation for various concepts and algorithms related to **surrogate modeling** and **surrogate-based optimization**. The jupyter-book has been created by the **Computational Design (CODE) Laboratory** led by **Prof. Leifur Leifsson** at **Purdue University**. This jupyter-book is intended to be used as a starting point for new users of surrogate methods to implement the concepts and algorithms for their own work uisng open source codes. The creation of this jupyter-book is funded partly by the National Science Foundation (NSF) award number 2223732.
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## Expected learning outcomes
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After going through this jupyter-book, the reader will:
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+ Have gained basic knowledge of surrogate methods and algorithms

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<section class="tex2jax_ignore mathjax_ignore" id="introduction">
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<h1>Introduction<a class="headerlink" href="#introduction" title="Permalink to this heading">#</a></h1>
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<p>This jupyter-book provides python implementation for various concepts and algorithms related to <strong>surrogate modeling</strong> and <strong>surrogate-based optimization</strong>. The jupyter-book has been created by the <strong>Computational Design (CODE) Laboratory</strong> led by <strong>Prof. Leifur Leifsson</strong> at <strong>Purdue University</strong>. This jupyter-book is intended to be used as a starting point for new users of surrogate methods to implement the concepts and algorithms for their own work uisng open source codes. The creation of this jupyter-book is funded partly by the National Science Foundation (NSF) award number 2223732.</p>
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<section id="expected-learning-outcomes">
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<h2>Expected learning outcomes<a class="headerlink" href="#expected-learning-outcomes" title="Permalink to this heading">#</a></h2>
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<p>After going through this jupyter-book, the reader will:</p>

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