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3 repository-uri

Awesome GitHub RepositoriesArray Initialization

Programmatic creation of multi-dimensional arrays using constants, identity matrices, or specific patterns.

Distinct from Multi-Dimensional Arrays: Focuses on the creation and initialization phase rather than the architectural implementation of multi-dimensional structures.

Explore 3 awesome GitHub repositories matching scientific & mathematical computing · Array Initialization. Refine with filters or upvote what's useful.

Awesome Array Initialization GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • nyandwi/machine_learning_completeAvatar Nyandwi

    Nyandwi/machine_learning_complete

    4,983Vezi pe GitHub↗

    This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi

    Demonstrates how to generate vectors and matrices using NumPy patterns like zeros and ones.

    Jupyter Notebookcomputer-visiondata-analysisdata-science
    Vezi pe GitHub↗4,983
  • dpilger26/numcppAvatar dpilger26

    dpilger26/NumCpp

    3,963Vezi pe GitHub↗

    NumCpp is a C++ framework and numerical computing library that provides a toolkit for multi-dimensional array management and mathematical routines. It functions as a C++ implementation of the NumPy ecosystem, offering a scientific computing framework for managing tensors and performing complex algebraic equations. The project enables high-performance array manipulation within a C++ environment without relying on a Python runtime. It distinguishes itself by providing a NumPy-like interface for executing linear algebra, managing multi-dimensional data structures, and performing numerical proces

    Offers programmatic creation of arrays using linear spacing, identity matrices, and fixed values.

    C++
    Vezi pe GitHub↗3,963
  • xtensor-stack/xtensorAvatar xtensor-stack

    xtensor-stack/xtensor

    3,748Vezi pe 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

    Creates arrays filled with constants, identity matrices, or sequences as lazy or evaluated containers.

    C++c-plus-plus-14multidimensional-arraysnumpy
    Vezi pe GitHub↗3,748
  1. Home
  2. Scientific & Mathematical Computing
  3. Multi-Dimensional Arrays
  4. Array Initialization

Explorează sub-etichetele

  • Template-Based InitializationCreation of arrays by mirroring the shape, type, and layout of an existing array. **Distinct from Array Initialization:** Distinct from general Array Initialization by focusing on cloning the structural properties of an existing tensor.