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index.html

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@@ -56,7 +56,7 @@ <h2 id="desc">An intro to Bayesian methods and probabilistic programming from a
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<div id="TOC">
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<ol>
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<li> <a href="#prolouge">Prolouge</a>
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<li> <a href="#prologue">Prologue</a>
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<li> <a href="#contents">Contents</a>
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<li> <a href="#examples">Examples</a>
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<li> <a href="#using-the-book">Reading and Installation</a>
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</div>
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<h2><a name="prolouge" class="anchor" href="#prolouge"><span class="octicon octicon-link"></span></a>Prolouge</h2>
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<h2><a name="prologue" class="anchor" href="#prologue"><span class="octicon octicon-link"></span></a>Prologue</h2>
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The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chapters of slow, mathematical analysis. The typical text on Bayesian inference involves two to three chapters on probability theory, then enters what Bayesian inference is. Unfortunately, due to mathematical intractability of most Bayesian models, the reader is only shown simple, artificial examples. This can leave the user with a <em>so-what</em> feeling about Bayesian inference. In fact, this was the author's own prior opinion.</p>
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