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<meta charset="utf-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
<meta name="description" content="GreatAI helps you easily transform your prototype AI code into production-ready software.">
<meta name="author" content="András Schmelczer">
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schmelczer/great-ai
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
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GitHub
schmelczer/great-ai
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<li class="md-nav__item">
<a href=".." class="md-nav__link">
Home
Overview
</a>
</li>
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<h1 id="train-a-domain-classifier-on-the-semantic-scholar-dataset">Train a domain classifier on the <a href="https://api.semanticscholar.org/corpus">semantic scholar dataset</a></h1>
<h1 id="train-a-domain-classifier-on-the-semantic-scholar-dataset">Train a domain classifier on the <a href="https://api.semanticscholar.org/corpus">semantic scholar dataset</a><a class="headerlink" href="#train-a-domain-classifier-on-the-semantic-scholar-dataset" title="Permanent link">#</a></h1>
<p><img alt="steps" src="diagrams/scope.svg" /></p>
<h2 id="install">Install</h2>
<h3 id="system-dependencies">System dependencies</h3>
<h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">#</a></h2>
<h3 id="system-dependencies">System dependencies<a class="headerlink" href="#system-dependencies" title="Permanent link">#</a></h3>
<p>Make sure you have <code>python3</code>, <code>pip</code>, and <code>venv</code> installed.</p>
<blockquote>
<p>On Ubuntu, execute: <code>sudo apt install -y python3 python3-pip python3-venv</code></p>
</blockquote>
<h3 id="install-dependencies">Install dependencies</h3>
<pre><code class="language-sh">python3 -m venv --copies .env
source .env/bin/activate
pip install -r requirements.txt
</code></pre>
<h2 id="execute">Execute</h2>
<h3 id="install-dependencies">Install dependencies<a class="headerlink" href="#install-dependencies" title="Permanent link">#</a></h3>
<div class="highlight"><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a>python3 -m venv --copies .env
<a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a><span class="nb">source</span> .env/bin/activate
<a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a>
<a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a>pip install -r requirements.txt
</code></pre></div>
<h2 id="execute">Execute<a class="headerlink" href="#execute" title="Permanent link">#</a></h2>
<ul>
<li><a href="src/data/">Part 1</a></li>
<li><a href="src/train/">Part 2</a></li>
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