<h1 id="lesson-4">Lesson 4<a aria-hidden="true" class="anchor-heading icon-link" href="#lesson-4"></a></h1>
<p><a href="https://youtu.be/toUgBQv1BT8">https://youtu.be/toUgBQv1BT8</a></p>
<h2 id="raw-notes">Raw notes<a aria-hidden="true" class="anchor-heading icon-link" href="#raw-notes"></a></h2>
<ul>
<li>ULMFit</li>
<li>Language model from wikipedia (wikitext 103)</li>
<li>Took pretrained model from wikipedia and ran a few epochs on IMDb</li>
<li>fine-tuned this for a classifier</li>
<li><a href="https://www.kaggle.com/code/jhoward/getting-started-with-nlp-for-absolute-beginners">https://www.kaggle.com/code/jhoward/getting-started-with-nlp-for-absolute-beginners</a>.</li>
<li>should learn numpy, pandas, matplotlib and pytorch.</li>
<li>Python for Data Analysis book - O'Reilly</li>
<li><code>df.describe(include='object')</code></li>
<li>think "what are some key features in this dataset?"</li>
<li><code>deberta-v3-small</code></li>
<li>TODO: what is SIMD?</li>
<li>Be careful using randomized validation sets.</li>
<li><a href="https://www.fast.ai/posts/2017-11-13-validation-sets.html">https://www.fast.ai/posts/2017-11-13-validation-sets.html</a></li>
<li>TODO: what is cross-validation?</li>
<li><a href="https://www.fast.ai/posts/2019-09-24-metrics.html">https://www.fast.ai/posts/2019-09-24-metrics.html</a></li>
</ul>
<hr>
<strong>Backlinks</strong>
<ul>
<li><a href="/notes/1uoml3dpen7vb528wa5pbw1">2023-03-24</a></li>
</ul>

Lesson 4


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