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  2. Delta encoding - Wikipedia

    en.wikipedia.org/wiki/Delta_encoding

    A delta can be defined in 2 ways, symmetric delta and directed delta.A symmetric delta can be expressed as (,) = (),where and represent two versions.. A directed delta, also called a change, is a sequence of (elementary) change operations which, when applied to one version , yields another version (note the correspondence to transaction logs in databases).

  3. Data structure alignment - Wikipedia

    en.wikipedia.org/wiki/Data_structure_alignment

    Data structure alignment is the way data is arranged and accessed in computer memory.It consists of three separate but related issues: data alignment, data structure padding, and packing.

  4. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    The Pandas and Polars Python libraries implement the Pearson correlation coefficient calculation as the default option for the methods pandas.DataFrame.corr and polars.corr, respectively. Wolfram Mathematica via the Correlation function, or (with the P value) with CorrelationTest. The Boost C++ library via the correlation_coefficient function.

  5. Softmax function - Wikipedia

    en.wikipedia.org/wiki/Softmax_function

    The Softmax function is a smooth approximation to the arg max function: the function whose value is the index of a vector's largest element. The name "softmax" may be misleading.

  6. List of IBM products - Wikipedia

    en.wikipedia.org/wiki/List_of_IBM_products

    Products, services, and subsidiaries have been offered from International Business Machines (IBM) Corporation and its predecessor corporations since the 1890s. [1] This list comprises those offerings and is eclectic; it includes, for example, the AN/FSQ-7, which was not a product in the sense of offered for sale, but was a product in the sense of manufactured—produced by the labor of IBM.

  7. Random forest - Wikipedia

    en.wikipedia.org/wiki/Random_forest

    Random forests are a way of averaging multiple deep decision trees, trained on different parts of the same training set, with the goal of reducing the variance. [ 3 ] : 587–588 This comes at the expense of a small increase in the bias and some loss of interpretability, but generally greatly boosts the performance in the final model.

  8. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a group of related models that are used to produce word embeddings.These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words.