reiver-artificial-intelligence/index.html

<article>
	<h1>Artificial Intelligence</h1>
	<section>
		<address class="h-card">
			by
			<a rel="author" class="u-url" href="http://changelog.ca/"><span class="p-given-name">Charles</span> <span class="p-additional-name">Iliya</span> <span class="p-family-name">Krempeaux</span></a>
		</address>
	</section>
	<section>
		<p>
			<strong>Artificial Intelligence</strong> (<abbr title="artificial intelligence">AI</abbr> is <ziba-link>intelligence</ziba-link> of <ziba-link>software</ziba-link> or a <ziba-link>machine</ziba-link>.
		</p>
	</section>
	<section>
		<h2>Index</h2>
		<section id="A">
			<h2>A</h2>
			<ul>
				<li><ziba-link transform="lowercase">a-a testing</ziba-link></li>
				<li><ziba-link transform="lowercase">a-b testing</ziba-link></li>
				<li><ziba-link>activation function</ziba-link></li>
				<li><ziba-link>artificial neural network</ziba-link></li>
			</ul>
		</section>
		<section id="B">
			<h2>B</h2>
			<ul>
				<li><ziba-link>back-propagation</ziba-link></li>
				<li><ziba-link>bandit</ziba-link></li>
				<li><ziba-link>big data</ziba-link></li>
				<li><ziba-link>business intelligence</ziba-link></li>
			</ul>
		</section>
		<section id="C">
			<h2>C</h2>
			<ul>
				<li><ziba-link>central limit theorem</ziba-link></li>
				<li><ziba-link>classification</ziba-link></li>
				<li><ziba-link>clustering</ziba-link></li>
				<li><ziba-link>computer vision</ziba-link></li>
				<li><ziba-link>curse of dimensionality</ziba-link></li>
			</ul>
		</section>
		<section id="D">
			<h2>D</h2>
			<ul>
				<li><ziba-link>data engineer</ziba-link></li>
				<li><ziba-link>data engineering</ziba-link></li>
				<li><ziba-link>data science</ziba-link></li>
				<li><ziba-link>data scientist</ziba-link></li>
				<li><ziba-link>database</ziba-link></li>
				<li><ziba-link>decision tree</ziba-link></li>
				<li><ziba-link>deep learning</ziba-link></li>
				<li><ziba-link>dirichlet distribution</ziba-link></li>
			</ul>
		</section>
		<section id="E">
			<h2>E</h2>
			<ul>
				<li><ziba-link>epsilon-greedy</ziba-link></li>
				<li><ziba-link>exploitation</ziba-link></li>
				<li><ziba-link>exploration</ziba-link></li>
				<li><ziba-link>exponential distribution</ziba-link></li>
			</ul>
		</section>
		<section id="F">
			<h2>F</h2>
			<ul>
				<li><ziba-link>feature</ziba-link></li>
				<li><ziba-link>feature engineering</ziba-link></li>
				<li><ziba-link>fraud detection</ziba-link></li>
			</ul>
		</section>
		<section id="G">
			<h2>G</h2>
			<ul>
				<li><ziba-link>gaussian distribution</ziba-link></li>
				<li><ziba-link>gradient descent</ziba-link></li>
				<li><ziba-link>ground truth</ziba-link></li>
			</ul>
		</section>
		<section id="H">
			<h2>H</h2>
		</section>
		<section id="I">
			<h2>I</h2>
		</section>
		<section id="J">
			<h2>J</h2>
		</section>
		<section id="K">
			<h2>K</h2>
			<ul>
				<li><ziba-link>k-means</ziba-link></li>
			</ul>
		</section>
		<section id="L">
			<h2>L</h2>
			<ul>
				<li><ziba-link>law of large numbers</ziba-link></li>
				<li><ziba-link>levels of measurement</ziba-link></li>
				<li><ziba-link>linear</ziba-link></li>
				<li><ziba-link>linear regression</ziba-link></li>
				<li><ziba-link>logistic function</ziba-link></li>
				<li><ziba-link>logistic regression</ziba-link></li>
			</ul>
		</section>
		<section id="M">
			<h2>M</h2>
			<ul>
				<li><ziba-link>machine</ziba-link></li>
				<li><ziba-link>machine learning</ziba-link></li>
				<li><ziba-link>machine learning engineer</ziba-link></li>
				<li><ziba-link>monte carlo simulation</ziba-link></li>
				<li><ziba-link>multi-armed bandit</ziba-link></li>
			</ul>
		</section>
		<section id="N">
			<h2>N</h2>
			<ul>
				<li><ziba-link>naive bayes</ziba-link></li>
				<li><ziba-link>natural language processing</ziba-link></li>
				<li><ziba-link>non-linear</ziba-link></li>
			</ul>
		</section>
		<section id="O">
			<h2>O</h2>
			<ul>
				<li><ziba-link>online advertising</ziba-link></li>
			</ul>
		</section>
		<section id="P">
			<h2>P</h2>
			<ul>
				<li><ziba-link>pareto distribution</ziba-link></li>
				<li><ziba-link>porter stemmer</ziba-link></li>
				<li><ziba-link>principal component analysis</ziba-link></li>
			</ul>
		</section>
		<section id="Q">
			<h2>Q</h2>
		</section>
		<section id="R">
			<h2>R</h2>
			<ul>
				<li><ziba-link>random forest</ziba-link></li>
				<li><ziba-link>recurrent neural network</ziba-link></li>
				<li><ziba-link>regression</ziba-link></li>
				<li><ziba-link>reinforcement learning</ziba-link></li>
			</ul>
		</section>
		<section id="S">
			<h2>S</h2>
			<ul>
				<li><ziba-link>softmax</ziba-link></li>
				<li><ziba-link>software</ziba-link></li>
				<li><ziba-link>sql</ziba-link></li>
				<li><ziba-link>stemming</ziba-link></li>
				<li><ziba-link>supervised learning</ziba-link></li>
				<li><ziba-link>support vector machine</ziba-link></li>
			</ul>
		</section>
		<section id="T">
			<h2>T</h2>
			<ul>
				<li><ziba-link>training</ziba-link></li>
			</ul>
		</section>
		<section id="U">
			<h2>U</h2>
			<ul>
				<li><ziba-link>unsupervised learning</ziba-link></li>
			</ul>
		</section>
		<section id="V">
			<h2>V</h2>
			<ul>
				<li><ziba-link>vector</ziba-link></li>
			</ul>
		</section>
		<section id="W">
			<h2>W</h2>
		</section>
		<section id="X">
			<h2>X</h2>
		</section>
		<section id="Y">
			<h2>Y</h2>
		</section>
		<section id="Z">
			<h2>Z</h2>
		</section>
	</section>
</article>