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  2. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...

  3. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.

  4. Stream processing - Wikipedia

    en.wikipedia.org/wiki/Stream_processing

    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.

  5. Category:Articles with example Python (programming language ...

    en.wikipedia.org/wiki/Category:Articles_with...

    Pages in category "Articles with example Python (programming language) code" The following 200 pages are in this category, out of approximately 201 total. This list may not reflect recent changes. (previous page)

  6. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    It supports macOS including Apple Silicon-based. It's a free compiler, though it also has commercial add-ons (e.g. for hiding source code). Numba is used from Python, as a tool (enabled by adding a decorator to relevant Python code), a JIT compiler that translates a subset of Python and NumPy code into fast machine code.

  7. Dataflow programming - Wikipedia

    en.wikipedia.org/wiki/Dataflow_programming

    POGOL, an otherwise conventional data-processing language developed at NSA, compiled large-scale applications composed of multiple file-to-file operations, e.g. merge, select, summarize, or transform, into efficient code that eliminated the creation of or writing to intermediate files to the greatest extent possible. [11]

  8. SciPy - Wikipedia

    en.wikipedia.org/wiki/SciPy

    SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [3]) is a free and open-source Python library used for scientific computing and technical computing. [4]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

  9. Data parallelism - Wikipedia

    en.wikipedia.org/wiki/Data_parallelism

    In an SPMD system executed on 2 processor system, both CPUs will execute the code. Data parallelism emphasizes the distributed (parallel) nature of the data, as opposed to the processing (task parallelism). Most real programs fall somewhere on a continuum between task parallelism and data parallelism.