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Keras contains numerous implementations of commonly used neural-network building blocks such as layers, objectives, activation functions, optimizers, and a host of tools for working with image and text data to simplify programming in deep neural network area. [11]
Often, the computer itself has no idea which piece of information encodes the enduring state. This is a serious problem, as the state information needs to be shared across multiple processors in parallel processing machines. Most languages force the programmer to add extra code to indicate which data and parts of the code are important to the ...
KNIME workflows can be used as data sets to create report templates that can be exported to document formats such as doc, ppt, xls, pdf and others. Other capabilities of KNIME are: KNIMEs core-architecture allows processing of large data volumes that are only limited by the available hard disk space (not limited to the available RAM). E.g.
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})
The name LISP derives from "List Processing language." Linked lists are one of the languages major data structures and Lisp source code is made of lists. Thus, Lisp programs can manipulate source code as a data structure, giving rise to the macro systems that allow programmers to create new syntax or even new domain-specific languages embedded ...
The first is an example of processing a data stream using a continuous SQL query (a query that executes forever processing arriving data based on timestamps and window duration). This code fragment illustrates a JOIN of two data streams, one for stock orders, and one for the resulting stock trades.
A programming language may be created for a specific task, but used beyond that original domain and thus be considered a general purpose programming language. For example, COBOL, Fortran, and Lisp were created as DSLs (for business processing, numeric computation, and symbolic processing), but became GPL's over time.
Data-centric programming language defines a category of programming languages where the primary function is the management and manipulation of data. A data-centric programming language includes built-in processing primitives for accessing data stored in sets, tables, lists, and other data structures and databases, and for specific manipulation and transformation of data required by a ...