226 lines
6.7 KiB
HTML
226 lines
6.7 KiB
HTML
<article>
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<h1>Artificial Intelligence</h1>
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<section>
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<address class="h-card">
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by
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<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>
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</address>
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</section>
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<section>
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<p>
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<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>.
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</p>
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</section>
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<section>
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<h2>Index</h2>
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<section id="A">
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<h2>A</h2>
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<ul>
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<li><ziba-link transform="lowercase">a-a testing</ziba-link></li>
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<li><ziba-link transform="lowercase">a-b testing</ziba-link></li>
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<li><ziba-link>activation function</ziba-link></li>
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<li><ziba-link>artificial neural network</ziba-link></li>
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</ul>
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</section>
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<section id="B">
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<h2>B</h2>
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<ul>
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<li><ziba-link>back-propagation</ziba-link></li>
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<li><ziba-link>bandit</ziba-link></li>
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<li><ziba-link>bayes rule</ziba-link></li>
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<li><ziba-link>bernoulli distribution</ziba-link></li>
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<li><ziba-link>big data</ziba-link></li>
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<li><ziba-link>binomial distribution</ziba-link></li>
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<li><ziba-link>business intelligence</ziba-link></li>
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</ul>
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</section>
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<section id="C">
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<h2>C</h2>
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<ul>
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<li><ziba-link>central limit theorem</ziba-link></li>
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<li><ziba-link>classification</ziba-link></li>
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<li><ziba-link>clustering</ziba-link></li>
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<li><ziba-link>computer vision</ziba-link></li>
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<li><ziba-link>curse of dimensionality</ziba-link></li>
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</ul>
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</section>
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<section id="D">
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<h2>D</h2>
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<ul>
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<li><ziba-link>data</ziba-link></li>
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<li><ziba-link>data engineer</ziba-link></li>
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<li><ziba-link>data engineering</ziba-link></li>
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<li><ziba-link>data science</ziba-link></li>
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<li><ziba-link>data scientist</ziba-link></li>
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<li><ziba-link>database</ziba-link></li>
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<li><ziba-link>datum</ziba-link></li>
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<li><ziba-link>decision tree</ziba-link></li>
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<li><ziba-link>deep learning</ziba-link></li>
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<li><ziba-link>dirichlet distribution</ziba-link></li>
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</ul>
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</section>
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<section id="E">
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<h2>E</h2>
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<ul>
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<li><ziba-link>empirical distribution</ziba-link></li>
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<li><ziba-link>epsilon-greedy</ziba-link></li>
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<li><ziba-link>evolutionary algorithm</ziba-link></li>
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<li><ziba-link>exploitation</ziba-link></li>
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<li><ziba-link>exploration</ziba-link></li>
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<li><ziba-link>exponential distribution</ziba-link></li>
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</ul>
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</section>
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<section id="F">
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<h2>F</h2>
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<ul>
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<li><ziba-link>feature</ziba-link></li>
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<li><ziba-link>feature engineering</ziba-link></li>
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<li><ziba-link>fraud detection</ziba-link></li>
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</ul>
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</section>
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<section id="G">
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<h2>G</h2>
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<ul>
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<li><ziba-link>gaussian distribution</ziba-link></li>
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<li><ziba-link>gaussian process</ziba-link></li>
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<li><ziba-link>genetic algorithm</ziba-link></li>
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<li><ziba-link>gradient descent</ziba-link></li>
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<li><ziba-link>ground truth</ziba-link></li>
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</ul>
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</section>
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<section id="H">
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<h2>H</h2>
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</section>
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<section id="I">
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<h2>I</h2>
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<ul>
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<li><ziba-link>interval data</ziba-link></li>
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</ul>
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</section>
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<section id="J">
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<h2>J</h2>
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</section>
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<section id="K">
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<h2>K</h2>
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<ul>
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<li><ziba-link>k-means</ziba-link></li>
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</ul>
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</section>
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<section id="L">
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<h2>L</h2>
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<ul>
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<li><ziba-link>law of large numbers</ziba-link></li>
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<li><ziba-link>levels of measurement</ziba-link></li>
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<li><ziba-link>likelihood</ziba-link></li>
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<li><ziba-link>linear</ziba-link></li>
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<li><ziba-link>linear regression</ziba-link></li>
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<li><ziba-link>logistic function</ziba-link></li>
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<li><ziba-link>logistic regression</ziba-link></li>
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</ul>
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</section>
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<section id="M">
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<h2>M</h2>
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<ul>
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<li><ziba-link>machine</ziba-link></li>
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<li><ziba-link>machine learning</ziba-link></li>
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<li><ziba-link>machine learning engineer</ziba-link></li>
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<li><ziba-link>mean</ziba-link></li>
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<li><ziba-link>monte carlo simulation</ziba-link></li>
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<li><ziba-link>modeling</ziba-link></li>
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<li><ziba-link>multi-armed bandit</ziba-link></li>
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</ul>
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</section>
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<section id="N">
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<h2>N</h2>
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<ul>
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<li><ziba-link>naive bayes</ziba-link></li>
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<li><ziba-link>natural language processing</ziba-link></li>
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<li><ziba-link>nominal data</ziba-link></li>
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<li><ziba-link>non-linear</ziba-link></li>
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</ul>
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</section>
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<section id="O">
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<h2>O</h2>
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<ul>
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<li><ziba-link>online advertising</ziba-link></li>
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<li><ziba-link>optical character recognition</ziba-link></li>
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<li><ziba-link>ordinal data</ziba-link></li>
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</ul>
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</section>
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<section id="P">
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<h2>P</h2>
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<ul>
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<li><ziba-link>pareto distribution</ziba-link></li>
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<li><ziba-link>porter stemmer</ziba-link></li>
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<li><ziba-link>posterior</ziba-link></li>
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<li><ziba-link>principal component analysis</ziba-link></li>
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<li><ziba-link>prior</ziba-link></li>
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<li><ziba-link>python programming language</ziba-link></li>
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</ul>
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</section>
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<section id="Q">
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<h2>Q</h2>
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<ul>
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<li><ziba-link>q-learning</ziba-link></li>
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<li><ziba-link>qualitative data</ziba-link></li>
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<li><ziba-link>quantitative data</ziba-link></li>
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</ul>
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</section>
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<section id="R">
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<h2>R</h2>
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<ul>
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<li><ziba-link>r programming language</ziba-link></li>
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<li><ziba-link>random forest</ziba-link></li>
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<li><ziba-link>ratio data</ziba-link></li>
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<li><ziba-link>recurrent neural network</ziba-link></li>
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<li><ziba-link>regression</ziba-link></li>
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<li><ziba-link>reinforcement learning</ziba-link></li>
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</ul>
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</section>
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<section id="S">
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<h2>S</h2>
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<ul>
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<li><ziba-link>softmax</ziba-link></li>
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<li><ziba-link>software</ziba-link></li>
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<li><ziba-link>sql</ziba-link></li>
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<li><ziba-link>stemming</ziba-link></li>
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<li><ziba-link>supervised learning</ziba-link></li>
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<li><ziba-link>support vector machine</ziba-link></li>
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</ul>
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</section>
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<section id="T">
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<h2>T</h2>
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<ul>
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<li><ziba-link>time series</ziba-link></li>
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<li><ziba-link>training</ziba-link></li>
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</ul>
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</section>
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<section id="U">
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<h2>U</h2>
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<ul>
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<li><ziba-link>unsupervised learning</ziba-link></li>
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</ul>
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</section>
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<section id="V">
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<h2>V</h2>
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<ul>
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<li><ziba-link>variance</ziba-link></li>
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<li><ziba-link>vector</ziba-link></li>
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<li><ziba-link>visualization</ziba-link></li>
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</ul>
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</section>
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<section id="W">
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<h2>W</h2>
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</section>
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<section id="X">
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<h2>X</h2>
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</section>
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<section id="Y">
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<h2>Y</h2>
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</section>
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<section id="Z">
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<h2>Z</h2>
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</section>
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</section>
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</article>
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