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2 repositorios

Awesome GitHub RepositoriesBasic Numeric Operations

Fundamental mathematical utilities for numeric data manipulation.

Distinct from Numerical Rounding: None of the candidates cover a general suite of basic arithmetic operations like absolute value, floor, and ceiling together.

Explore 2 awesome GitHub repositories matching scientific & mathematical computing · Basic Numeric Operations. Refine with filters or upvote what's useful.

Awesome Basic Numeric Operations GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • lyhue1991/eat_tensorflow2_in_30_daysAvatar de lyhue1991

    lyhue1991/eat_tensorflow2_in_30_days

    9,933Ver en GitHub↗

    This project is a structured learning curriculum and technical reference for mastering deep learning with TensorFlow. It provides a comprehensive guide for building, training, and deploying neural networks, combining theoretical fundamentals with practical implementation examples. The repository distinguishes itself by covering the end-to-end machine learning workflow, from low-level tensor mathematics and linear algebra to the creation of complex model architectures. It includes specific guidance on developing data pipelines for diverse data types, such as images, text, and time-series seque

    Conducts low-level mathematical operations and custom numeric calculations essential for deep learning research.

    Pythontensorflowtensorflow-examplestensorflow-tutorial
    Ver en GitHub↗9,933
  • xtensor-stack/xtensorAvatar de xtensor-stack

    xtensor-stack/xtensor

    3,748Ver en GitHub↗

    xtensor is a C++ multidimensional array library for numerical computing that provides N-dimensional containers with an interface mirroring the NumPy API. It utilizes a lazy evaluation expression engine to defer numerical computations until assignment, which minimizes memory allocations and intermediate copies. The library features a foreign memory array adaptor that allows it to wrap external buffers, such as NumPy arrays, to perform numerical operations in-place without duplicating data. It further optimizes performance through lazy broadcasting and a system that manages the lifetime of temp

    Implements fundamental mathematical utilities such as absolute values, signs, and element clipping for numeric data.

    C++c-plus-plus-14multidimensional-arraysnumpy
    Ver en GitHub↗3,748
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