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Mathematical and programmatic operations for reshaping, filtering, and transforming multi-dimensional data structures.
Explore 92 awesome GitHub repositories matching data & databases · Array and Tensor Manipulation. Refine with filters or upvote what's useful.
TensorFlow is a comprehensive machine learning framework designed for the construction, training, and deployment of complex mathematical models. It utilizes a graph-based execution model that represents operations as directed acyclic graphs, enabling automatic differentiation and efficient parallel processing. The system provides high-level interfaces for defining neural network architectures, alongside a robust engine for managing multidimensional array structures and tensor mathematics. The framework distinguishes itself through a scalable distributed runtime that orchestrates workloads acr
Applies optimized routines to perform element-wise operations and shape manipulations on multi-dimensional data structures.
n8n is a workflow automation platform that combines a visual interface with code-based extensibility to design, orchestrate, and manage automated processes. It provides a comprehensive suite of tools for data transformation, filtering, and storage, allowing users to build complex logic through conditional branching, looping, and sub-workflow execution. The platform supports both pre-built integration nodes and custom code execution in JavaScript or Python, enabling connectivity with a wide range of external services and APIs. The platform includes a suite of generative AI capabilities, such a
Refines nested data structures by applying programmatic expressions to isolate specific elements within arrays.
D3 is a modular library providing low-level primitives for creating data-driven visualizations. It functions as a flexible framework that allows for direct control over visual presentation by mapping abstract data dimensions to graphical properties, such as position, color, and size, without imposing predefined chart abstractions. The library distinguishes itself by offering specialized tools for complex data representation, including algorithmic layouts for hierarchical structures and geographic projection utilities for mapping spherical coordinates. It also includes a comprehensive suite fo
Comprehensive utilities handle the ordering, searching, summarizing, binning, and grouping of complex data sets.
This project is an open-source, interactive educational platform designed to teach deep learning through a comprehensive, code-first curriculum. It provides a structured learning path that covers foundational mathematics, modern neural network architectures, and practical optimization techniques, enabling practitioners to master complex artificial intelligence concepts through hands-on experimentation. The platform distinguishes itself by integrating technical explanations with executable Jupyter notebooks. This design allows readers to modify code and hyperparameters in real-time, facilitati
Wraps complex tensor operations into accessible tutorials for reshaping and transforming multidimensional data.
Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying models for object detection, image segmentation, and visual recognition. It provides a research-oriented environment for training complex vision models with multi-GPU acceleration. The project includes a specialized object detection library for identifying and locating multiple objects via bounding boxes, as well as an image segmentation toolkit for creating pixel-level masks through instance, semantic, and panoptic segmentation. Additionally, it features a human pose estimati
Converts raw image annotations into standardized tensor formats for consistent model training.
This project is an educational platform and research toolkit designed to teach deep learning through a combination of mathematical theory, visual diagrams, and executable code. It provides a comprehensive environment for building, training, and evaluating neural networks, grounding complex concepts in interactive computational notebooks that allow for hands-on experimentation. The framework distinguishes itself by interleaving theoretical foundations—including linear algebra, calculus, and probability—with practical implementations across multiple industry-standard libraries. It supports flex
Provides indexing, slicing, and broadcasting for high-dimensional data manipulation.
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
Creates memory-efficient array views that reinterpret data without explicit copies.
core-js is a comprehensive compatibility layer and standard library polyfill that implements ECMAScript proposals and stable language features across diverse JavaScript runtimes. It serves as a runtime environment shim to ensure consistent execution of global objects, iteration protocols, and standard library methods in older browsers or non-browser environments. The project is distinguished by its delivery models, offering both prototype-based global polyfilling and a pure-module implementation. This allows for the integration of modern functionality without modifying global prototypes to pr
Implements logic to organize array elements into maps or objects based on shared keys.
This project is a comprehensive JavaScript programming tutorial and language reference. It serves as a web development education resource providing instruction on modern language fundamentals, object-oriented design, and advanced asynchronous programming patterns. The resource functions as both a frontend development guide and a technical reference. It covers core language features such as closures, prototypes, promises, and typed arrays, while providing practical lessons on managing browser data and handling network requests. The content spans several key capability areas, including browser
Provides instruction on using programmatic expressions to filter specific elements within arrays.
Paddle is a deep learning framework designed for building, training, and deploying neural networks. It provides a platform for constructing models using tensor-based computations and supports both dynamic and static execution graphs to facilitate research and production workflows. The platform functions as a distributed machine learning system, enabling the scaling of training workloads across multiple nodes and hardware clusters. It includes a comprehensive toolkit for model deployment and optimization, allowing users to convert external model formats, compress trained models for resource-co
Provides mathematical and programmatic operations for reshaping and transforming multi-dimensional tensor data.
Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network
Performs operations on arrays such as appending, pushing, popping, and zipping elements to restructure event data.
This project is a comprehensive educational resource and technical documentation suite for learning and developing deep learning models. It serves as an open-source textbook, implementation manual, and framework tutorial designed to guide users through the mathematical foundations and practical application of neural networks. The resource provides detailed instructional content on building various model architectures, including convolutional and recurrent neural networks. It includes a dedicated distributed training guide and a learning path that covers the fundamentals of tensors, automatic
Covers programmatic operations for reshaping, filtering, and transforming multi-dimensional tensors to organize data for models.
This project is a deep learning framework designed for constructing, training, and deploying neural networks across diverse hardware environments. It functions as a high-performance tensor computation library that provides both imperative and symbolic programming interfaces, allowing developers to balance flexible, step-by-step model building with the efficiency of compiled computation graphs. The framework distinguishes itself through a hybrid execution engine that integrates declarative graph compilation with imperative runtime logic. It supports scalable, distributed training across multip
Provides high-performance interfaces for manipulating multi-dimensional tensors and performing complex numerical computations.
Blender is a professional 3D creation suite designed for modeling, animation, rendering, and video editing. It functions as an open-source 3D engine that provides a comprehensive framework for procedural geometry, physics simulation, and high-quality visual output. The platform is built upon a foundational architecture that utilizes data-block-based memory management and a dependency-graph-based evaluation system to handle complex scene transformations and geometry updates. The software distinguishes itself through a highly modular, node-based procedural architecture that allows users to cons
Filters data collections using indices and predicates to optimize processing performance.
AirSim is a high-fidelity simulation platform designed for the development and testing of autonomous vehicles. Built as a plugin for game engines, it provides a physics-based environment that models vehicle dynamics and sensor data, serving as a foundation for robotics research, computer vision training, and reinforcement learning. The platform distinguishes itself through its support for hardware-in-the-loop and software-in-the-loop testing, allowing developers to validate control logic and firmware against real-world signals or concurrent processes. It offers extensive programmatic control
Discretizes 3D environments into occupancy grids to represent occupied space for navigation.
classnames is a JavaScript utility for conditionally joining CSS class names into a single space-separated string. It functions as a class name manager that maps boolean flags and objects to specific styles for HTML attribute assignment. The tool resolves abstract class identifiers to computed values, facilitating integration with modular styling systems. It allows for the mapping of dynamic identifiers to scoped class names through a dedicated module resolver. The utility processes strings, arrays, and objects to handle dynamic class name management. It includes capabilities for recursive a
Flattens nested arrays of class names into a single-level sequence before joining.
Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing
Performs set operations, statistical calculations, and sorting on array elements to transform complex data structures.
This project is a comprehensive educational resource and programming course covering C++ language semantics and features from C++03 through C++26. It provides structured tutorials and technical guides focused on modern C++ development. The material offers specialized instruction on template metaprogramming, including the use of type traits and compile-time computations. It features detailed guides on concurrency and parallelism for multi-core execution, as well as a reference for software design applying SOLID principles and RAII. Additionally, it covers build performance optimization to redu
Details how to create non-owning views over contiguous sequences to avoid expensive data copying.
gjson is a Go JSON parser designed for schema-less reading and value extraction. It allows for the retrieval of specific data from JSON documents using dot-notation paths without requiring the definition of predefined Go structs. The library provides tools for path-based querying, including the use of wildcards and index-based queries to locate data within objects and arrays. It also functions as a JSON lines processor, treating multi-line documents as arrays to iterate and query individual entries. Additional capabilities include converting JSON values into native Go types such as strings,
Filters array elements using comparison operators and pattern matching to find specific matches.
This tool is a command-line processor designed for querying, updating, and transforming structured data files. It functions as a versatile engine for manipulating YAML, JSON, TOML, and XML documents, allowing users to perform complex operations directly from the terminal. By utilizing a path-based expression language, it enables precise navigation and modification of data structures within configuration files and infrastructure-as-code workflows. What distinguishes this tool is its ability to perform in-place document mutations while preserving original formatting, comments, and metadata. It
The tool recursively collapses multi-dimensional arrays into a single-level list by extracting all elements into the top-level sequence.