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Frequency lists are a useful tool when building an electronic dictionary, which is a prerequisite for a wide range of applications in computational linguistics. German linguists define the Häufigkeitsklasse (frequency class) N {\displaystyle N} of an item in the list using the base 2 logarithm of the ratio between its frequency and the ...
Beyond reserving specific lists of words, some languages reserve entire ranges of words, for use as private spaces for future language version, different dialects, compiler vendor-specific extensions, or for internal use by a compiler, notably in name mangling. This is most often done by using a prefix, often one or more underscores.
Another meaning of range in computer science is an alternative to iterator. When used in this sense, range is defined as "a pair of begin/end iterators packed together". [1] It is argued [1] that "Ranges are a superior abstraction" (compared to iterators) for several reasons, including better safety.
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
Python and Ruby both recommend UpperCamelCase for class names, CAPITALIZED_WITH_UNDERSCORES for constants, and snake_case for other names. In Python, if a name is intended to be "private", it is prefixed by one or two underscores. Private variables are enforced in Python only by convention.
Also simply application or app. Computer software designed to perform a group of coordinated functions, tasks, or activities for the benefit of the user. Common examples of applications include word processors, spreadsheets, accounting applications, web browsers, media players, aeronautical flight simulators, console games, and photo editors. This contrasts with system software, which is ...
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. The word2vec algorithm estimates these representations by modeling text in a large corpus.
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.