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< title > Artificial Intelligence< / title >
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< h1 > Artificial Intelligence< / h1 >
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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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< strong > Artificial Intelligence< / strong > (< abbr title = "artificial intelligence" > AI< / abbr > ) is < a href = "intelligence/" > intelligence< / a > of < a href = "software/" > software< / a > or a < a href = "machine/" > machine< / a > .
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< strong > Artificial Intelligence< / strong > is usually considered a sub-topic of < strong > computing< / strong > .
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If you are new to < strong > Artificial Intelligence< / strong > , start with the < a href = "introduction/" > introduction< / a > .
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< h2 > Index< / h2 >
< section id = "A" >
< h2 > A< / h2 >
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< li > < a href = "a-a-testing/" > a a testing< / a > < / li >
< li > < a href = "a-b-testing/" > a b testing< / a > < / li >
< li > < a href = "activation-function/" > activation-function< / a > < / li >
< li > < a href = "artificial-neural-network/" > artificial-neural-network< / a > < / li >
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< h2 > B< / h2 >
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< li > < a href = "back-propagation/" > back-propagation< / a > < / li >
< li > < a href = "bandit/" > bandit< / a > < / li >
< li > < a href = "bayes-rule/" > bayes-rule< / a > < / li >
< li > < a href = "bernoulli-distribution/" > bernoulli-distribution< / a > < / li >
< li > < a href = "big-data/" > big-data< / a > < / li >
< li > < a href = "binomial-distribution/" > binomial-distribution< / a > < / li >
< li > < a href = "business-intelligence/" > business-intelligence< / a > < / li >
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< section id = "C" >
< h2 > C< / h2 >
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< li > < a href = "central-limit-theorem/" > central-limit-theorem< / a > < / li >
< li > < a href = "classification/" > classification< / a > < / li >
< li > < a href = "clustering/" > clustering< / a > < / li >
< li > < a href = "computer-vision/" > computer-vision< / a > < / li >
< li > < a href = "curse-of-dimensionality/" > curse-of-dimensionality< / a > < / li >
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< section id = "D" >
< h2 > D< / h2 >
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< li > < a href = "data/" > data< / a > < / li >
< li > < a href = "data-engineer/" > data-engineer< / a > < / li >
< li > < a href = "data-engineering/" > data-engineering< / a > < / li >
< li > < a href = "data-science/" > data-science< / a > < / li >
< li > < a href = "data-scientist/" > data-scientist< / a > < / li >
< li > < a href = "database/" > database< / a > < / li >
< li > < a href = "datum/" > datum< / a > < / li >
< li > < a href = "decision-tree/" > decision-tree< / a > < / li >
< li > < a href = "deep-learning/" > deep-learning< / a > < / li >
< li > < a href = "dirichlet-distribution/" > dirichlet-distribution< / a > < / li >
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< section id = "E" >
< h2 > E< / h2 >
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< li > < a href = "empirical-distribution/" > empirical-distribution< / a > < / li >
< li > < a href = "epsilon-greed/" > epsilon-greedy< / a > < / li >
< li > < a href = "evolutionary-algorithm/" > evolutionary-algorithm< / a > < / li >
< li > < a href = "exploitation/" > exploitation< / a > < / li >
< li > < a href = "exploration/" > exploration< / a > < / li >
< li > < a href = "exponential-distribution/" > exponential-distribution< / a > < / li >
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< section id = "F" >
< h2 > F< / h2 >
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< li > < a href = "feature/" > feature< / a > < / li >
< li > < a href = "feature-engineering/" > feature-engineering< / a > < / li >
< li > < a href = "fraud-detection/" > fraud-detection< / a > < / li >
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< section id = "G" >
< h2 > G< / h2 >
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< li > < a href = "gaussian-distribution/" > gaussian-distribution< / a > < / li >
< li > < a href = "gaussian-process/" > gaussian-process< / a > < / li >
< li > < a href = "genetic-algorithm/" > genetic-algorithm< / a > < / li >
< li > < a href = "gradient-descent/" > gradient-descent< / a > < / li >
< li > < a href = "ground-truth/" > ground-truth< / a > < / li >
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< section id = "H" >
< h2 > H< / h2 >
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< section id = "I" >
< h2 > I< / h2 >
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< li > < a href = "interval-data/" > interval-data< / a > < / li >
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< li > < a href = "introduction/" > introduction< / a > < / li >
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< section id = "J" >
< h2 > J< / h2 >
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< section id = "K" >
< h2 > K< / h2 >
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< li > < a href = "k-means/" > k-means< / a > < / li >
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< section id = "L" >
< h2 > L< / h2 >
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< li > < a href = "law-of-large-numbers/" > law-of-large-numbers< / a > < / li >
< li > < a href = "levels-of-measurement/" > levels-of-measurement< / a > < / li >
< li > < a href = "likelihood/" > likelihood< / a > < / li >
< li > < a href = "linear/" > linear< / a > < / li >
< li > < a href = "linear-regression/" > linear-regression< / a > < / li >
< li > < a href = "logistic-function/" > logistic-function< / a > < / li >
< li > < a href = "logistic-regression/" > logistic-regression< / a > < / li >
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< section id = "M" >
< h2 > M< / h2 >
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< li > < a href = "machine/" > machine< / a > < / li >
< li > < a href = "machine-learning/" > machine-learning< / a > < / li >
< li > < a href = "machine-learning-engineer/" > machine-learning-engineer< / a > < / li >
< li > < a href = "mean/" > mean< / a > < / li >
< li > < a href = "monte-carlo-simulation/" > monte-carlo-simulation< / a > < / li >
< li > < a href = "modeling/" > modeling< / a > < / li >
< li > < a href = "multi-armed-bandit/" > multi-armed-bandit< / a > < / li >
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< section id = "N" >
< h2 > N< / h2 >
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< li > < a href = "naive-bayes/" > naive-bayes< / a > < / li >
< li > < a href = "natural-language-processing/" > natural-language-processing< / a > < / li >
< li > < a href = "nominal-data/" > nominal-data< / a > < / li >
< li > < a href = "non-linear/" > non-linear< / a > < / li >
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< section id = "O" >
< h2 > O< / h2 >
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< li > < a href = "online-advertising/" > online-advertising< / a > < / li >
< li > < a href = "optical-character-recognition/" > optical-character-recognition< / a > < / li >
< li > < a href = "ordinal-data/" > ordinal-data< / a > < / li >
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< section id = "P" >
< h2 > P< / h2 >
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< li > < a href = "pareto-distribution/" > pareto-distribution< / a > < / li >
< li > < a href = "porter-stemmer/" > porter-stemmer< / a > < / li >
< li > < a href = "posterior/" > posterior< / a > < / li >
< li > < a href = "principal-component-analysis/" > principal-component-analysis< / a > < / li >
< li > < a href = "prior/" > prior< / a > < / li >
< li > < a href = "python-programming-language/" > python-programming-language< / a > < / li >
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< section id = "Q" >
< h2 > Q< / h2 >
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< li > < a href = "q-learning/" > q-learning< / a > < / li >
< li > < a href = "qualitative-data/" > qualitative-data< / a > < / li >
< li > < a href = "quantitative-data/" > quantitative-data< / a > < / li >
< li > < a href = "qualitative-research/" > qualitative-research< / a > < / li >
< li > < a href = "quantitative-research/" > quantitative-research< / a > < / li >
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< section id = "R" >
< h2 > R< / h2 >
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< li > < a href = "r-programming-language/" > r-programming-language< / a > < / li >
< li > < a href = "random-forest/" > random-forest< / a > < / li >
< li > < a href = "ratio-data/" > ratio-data< / a > < / li >
< li > < a href = "recurrent-neural-network/" > recurrent-neural-network< / a > < / li >
< li > < a href = "regression/" > regression< / a > < / li >
< li > < a href = "reinforcement-learning/" > reinforcement-learning< / a > < / li >
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< section id = "S" >
< h2 > S< / h2 >
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< li > < a href = "softmax/" > softmax< / a > < / li >
< li > < a href = "software/" > software< / a > < / li >
< li > < a href = "sql/" > sql< / a > < / li >
< li > < a href = "stemming/" > stemming< / a > < / li >
< li > < a href = "supervised-learning/" > supervised-learning< / a > < / li >
< li > < a href = "support-vector-machine/" > support-vector-machine< / a > < / li >
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< section id = "T" >
< h2 > T< / h2 >
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< li > < a href = "time-series/" > time-series< / a > < / li >
< li > < a href = "training/" > training< / a > < / li >
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< section id = "U" >
< h2 > U< / h2 >
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< li > < a href = "unsupervised-learning/" > unsupervised-learning< / a > < / li >
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< section id = "V" >
< h2 > V< / h2 >
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< li > < a href = "variance/" > variance< / a > < / li >
< li > < a href = "vector/" > vector< / a > < / li >
< li > < a href = "visualization/" > visualization< / a > < / li >
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< section id = "W" >
< h2 > W< / h2 >
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< section id = "X" >
< h2 > X< / h2 >
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< section id = "Y" >
< h2 > Y< / h2 >
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< section id = "Z" >
< h2 > Z< / h2 >
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