4 مستودعات
Dense data structures supporting various memory layouts and dimensionality for numerical computing.
Distinct from C Tensor Libraries: None of the candidates provide a general-purpose multidimensional tensor container identity; others are too low-level or specific to C/GPU memory.
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This project is a collection of pre-trained machine learning models and conversion pipelines designed for running inference directly in the browser using TensorFlow.js. It provides a library of ready-to-use models for computer vision, audio classification, and natural language processing tasks. The suite includes specialized tools for transforming Python-based Keras models into JSON formats compatible with web environments. It enables the deployment of these models by fetching architectures and weight shards via HTTP for client-side execution. The project covers a broad range of capabilities
Initializes data buffers of various shapes from arrays to perform complex mathematical computations.
This project is an educational resource and a collection of instructional materials for performing data manipulation and statistical analysis using Python. It provides a comprehensive set of guides and code examples for using the Pandas, NumPy, and Matplotlib libraries to analyze structured data. The resource includes a dedicated guide for reshaping, cleaning, and aggregating tabular data and time series via Pandas, alongside a reference for high-performance vectorized operations and linear algebra using NumPy. It also features tutorials for creating publication-quality charts, distribution p
Generates n-dimensional array containers from sequences or predefined shapes for efficient storage.
ndarray هي مكتبة مصفوفات متعددة الأبعاد لـ Rust تعمل كإطار عمل للجبر الخطي وأداة للحوسبة العلمية. توفر البنية التحتية الأساسية لإنشاء ومعالجة المصفوفات n-الأبعاد، وتعمل كمعالج مصفوفات متوازي ومجموعة أدوات لتحليل البيانات الرقمية. تتميز المكتبة بتوفير تقطيع (slicing) وعروض ذاكرة فعالة، مما يسمح بمشاركة البيانات دون نسخ. تستفيد من مكتبات الرياضيات الخلفية المحسنة لضرب المصفوفات عالي السرعة وتوزع التكرارات الرياضية الثقيلة عبر خيوط CPU متعددة لتسريع المعالجة. يغطي المشروع مجموعة واسعة من العمليات الرياضية، بما في ذلك الحساب العنصري، وتجميع البيانات القائم على المحور، وحسابات الضرب النقطي. كما يتضمن أدوات شاملة لمعالجة المصفوفات مثل إعادة التشكيل، والتسطيح، والتكديس، وتوليد شبكة الإحداثيات، إلى جانب دعم توليد المصفوفات العشوائية والتسلسل.
Offers dense data structures supporting various memory layouts for numerical computing and data analysis.
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
Provides a dense multidimensional container supporting row-major and column-major layouts with dynamic or static dimensionality.