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However, note that performance suffers when there are more than 100 alternatives. Placing common values earlier in the list of cases can cause the function to execute significantly faster. For each case, either side of the equals sign "=" can be a simple string, a call to a parser function (including #expr to evaulate expressions), or a ...
The following table lists many common symbols, together with their name, how they should be read out loud, and the related field of mathematics. Additionally, the subsequent columns contains an informal explanation, a short example, the Unicode location, the name for use in HTML documents, [1] and the LaTeX symbol.
Algebraic laws for regular expressions can be obtained using a method by Gischer which is best explained along an example: In order to check whether (X+Y) * and (X * Y *) * denote the same regular language, for all regular expressions X, Y, it is necessary and sufficient to check whether the particular regular expressions (a+b) * and (a * b ...
To list terms and definitions, start a new line with a semicolon (;) followed by the term. Then, type a colon (:) followed by a definition. The format can also be used for other purposes, such as make and models of vehicles, etc. Description lists (formerly definition lists, and a.k.a. association lists) consist of group names corresponding to ...
Most commonly a data set corresponds to the contents of a single database table, or a single statistical data matrix, where every column of the table represents a particular variable, and each row corresponds to a given member of the data set in question. The data set lists values for each of the variables, such as height and weight of an ...
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YAML (/ ˈ j æ m əl /, rhymes with camel [4]) was first proposed by Clark Evans in 2001, [15] who designed it together with Ingy döt Net [16] and Oren Ben-Kiki. [16]Originally YAML was said to mean Yet Another Markup Language, [17] because it was released in an era that saw a proliferation of markup languages for presentation and connectivity (HTML, XML, SGML, etc.).
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.