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<title>Chapter 18 Python notebooks | Machine Learning for Factor Investing</title>
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<nav aria-label="Table of contents"><h2>Table of contents</h2>
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<li><a class="" href="index.html">Preface</a></li>
<li class="book-part">Introduction</li>
<li><a class="" href="notdata.html"><span class="header-section-number">1</span> Notations and data</a></li>
<li><a class="" href="intro.html"><span class="header-section-number">2</span> Introduction</a></li>
<li><a class="" href="factor.html"><span class="header-section-number">3</span> Factor investing and asset pricing anomalies</a></li>
<li><a class="" href="Data.html"><span class="header-section-number">4</span> Data preprocessing</a></li>
<li class="book-part">Common supervised algorithms</li>
<li><a class="" href="lasso.html"><span class="header-section-number">5</span> Penalized regressions and sparse hedging for minimum variance portfolios</a></li>
<li><a class="" href="trees.html"><span class="header-section-number">6</span> Tree-based methods</a></li>
<li><a class="" href="NN.html"><span class="header-section-number">7</span> Neural networks</a></li>
<li><a class="" href="svm.html"><span class="header-section-number">8</span> Support vector machines</a></li>
<li><a class="" href="bayes.html"><span class="header-section-number">9</span> Bayesian methods</a></li>
<li class="book-part">From predictions to portfolios</li>
<li><a class="" href="valtune.html"><span class="header-section-number">10</span> Validating and tuning</a></li>
<li><a class="" href="ensemble.html"><span class="header-section-number">11</span> Ensemble models</a></li>
<li><a class="" href="backtest.html"><span class="header-section-number">12</span> Portfolio backtesting</a></li>
<li class="book-part">Further important topics</li>
<li><a class="" href="interp.html"><span class="header-section-number">13</span> Interpretability</a></li>
<li><a class="" href="causality.html"><span class="header-section-number">14</span> Two key concepts: causality and non-stationarity</a></li>
<li><a class="" href="unsup.html"><span class="header-section-number">15</span> Unsupervised learning</a></li>
<li><a class="" href="RL.html"><span class="header-section-number">16</span> Reinforcement learning</a></li>
<li class="book-part">Appendix</li>
<li><a class="" href="data-description.html"><span class="header-section-number">17</span> Data description</a></li>
<li><a class="active" href="python.html"><span class="header-section-number">18</span> Python notebooks</a></li>
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<span class="header-section-number">18.1</span> Python notebooks: chapter 1<a class="anchor" aria-label="anchor" href="#python"><i class="fas fa-link"></i></a>
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<p>"<strong>Machine Learning for Factor Investing</strong>" was written by Guillaume Coqueret and Tony Guida. It was last built on 2021-05-25.</p>
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