5 个仓库
Retrieves metadata including data types, dimensions, and floating-point limits.
Distinct from Data Type Inspection: Focuses on metadata inspection, distinct from schema-level type inspection.
Explore 5 awesome GitHub repositories matching data & databases · Array Inspection. Refine with filters or upvote what's useful.
This project is a machine learning array framework and tensor computation library designed for high-performance numerical computing. It provides a comprehensive suite of tools for constructing and training neural networks, featuring an automatic differentiation engine that facilitates gradient-based optimization and complex mathematical modeling. The library distinguishes itself through a unified memory architecture that allows data to be shared across CPU and GPU devices without explicit copies, significantly reducing data movement overhead. Its execution model relies on a lazy evaluation en
Exposes array metadata to assist in numerical precision and range calculations.
This project is a curated collection of programming exercises designed to build proficiency in numerical computing and data manipulation. It provides a structured learning path for mastering multidimensional array operations, vectorized arithmetic, and statistical analysis. The repository focuses on developing practical expertise in array-based workflows, emphasizing techniques such as memory management, efficient data processing, and the replacement of explicit loops with vectorized operations. Users engage with hands-on challenges that cover the full lifecycle of numerical data, from initia
Retrieves metadata including data types, dimensions, and floating-point limits for array inspection.
本项目是一个机器学习教育课程和学习平台,通过交互式 Jupyter Notebooks 提供。它作为掌握 Python 数据科学工具包的综合指南,为数值计算、表格数据操作和统计可视化提供结构化教程。 该课程包括 Scikit-Learn 的具体实现指南,以及关于构建、训练和部署神经网络及计算机视觉模型的 TensorFlow 实践课程。它涵盖了构建预测模型的端到端过程,从初始问题定义和任务分类,到通过交互式 Web 界面部署模型。 该项目涵盖了广泛的功能领域,包括多维数组的数值计算、探索性数据分析和数据预处理例程。它为监督和无监督学习、自动化机器学习流水线、超参数优化以及使用分类指标和交叉验证的模型评估提供了详细的工作流。 教育内容组织为一系列 Notebook,将 Python 代码与叙述性解释交织在一起,以记录数据科学工作流。
Provides capabilities for retrieving metadata including data types and dimensions from numerical arrays.
Orange3 is a visual data mining platform that provides an interactive canvas for building data analysis workflows without writing code. At its core, it offers a widget-based visual programming environment where users connect configurable components to perform data preprocessing, machine learning model training, statistical evaluation, and interactive visualization. The platform is built on NumPy-backed data tables with domain descriptors that define variable names, types, and roles, and includes a lazy SQL query proxy for working with database tables without loading all data into memory. The
Provides a method to inspect whether data arrays are stored as dense or sparse representations.
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
Retrieves metadata including total size, dimension count, and axis lengths for array expressions.