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  2. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    Contents. NumPy. NumPy (pronounced / ˈnʌmpaɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [ 3 ] The predecessor of NumPy, Numeric, was originally created by Jim Hugunin ...

  3. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values. For example, if s is a Series, s['a'] will return the data point at index a. Unlike dictionary keys, index values are ...

  4. Comparison of statistical packages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_statistical...

    Comparison of computer algebra systems. Comparison of deep learning software. Comparison of numerical-analysis software. Comparison of survey software. Comparison of Gaussian process software. List of scientific journals in statistics. List of statistical packages.

  5. Array slicing - Wikipedia

    en.wikipedia.org/wiki/Array_slicing

    This article is about the data structure operation. For other uses of slicing, see Slicing (disambiguation). In computer programming, array slicing is an operation that extracts a subset of elements from an array and packages them as another array, possibly in a different dimension from the original. Common examples of array slicing are ...

  6. Array (data type) - Wikipedia

    en.wikipedia.org/wiki/Array_(data_type)

    In computer science, array is a data type that represents a collection of elements (values or variables), each selected by one or more indices (identifying keys) that can be computed at run time during program execution. Such a collection is usually called an array variable or array value. [ 1 ] By analogy with the mathematical concepts vector ...

  7. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    Fisher–Yates shuffle. The Fisher–Yates shuffle is an algorithm for shuffling a finite sequence. The algorithm takes a list of all the elements of the sequence, and continually determines the next element in the shuffled sequence by randomly drawing an element from the list until no elements remain. [ 1 ] The algorithm produces an unbiased ...

  8. XGBoost - Wikipedia

    en.wikipedia.org/wiki/XGBoost

    XGBoost works as Newton-Raphson in function space unlike gradient boosting that works as gradient descent in function space, a second order Taylor approximation is used in the loss function to make the connection to Newton Raphson method. A generic unregularized XGBoost algorithm is:

  9. Basic Linear Algebra Subprograms - Wikipedia

    en.wikipedia.org/wiki/Basic_Linear_Algebra...

    Basic Linear Algebra Subprograms (BLAS) is a specification that prescribes a set of low-level routines for performing common linear algebra operations such as vector addition, scalar multiplication, dot products, linear combinations, and matrix multiplication. They are the de facto standard low-level routines for linear algebra libraries; the ...