Showing 6 open source projects for "data fit"

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  • 1
    Yangshun Lago

    Yangshun Lago

    Data Structures and Algorithms library in TypeScript and JavaScript

    Lago is a study-oriented library of classic data structures and algorithms implemented in JavaScript with an emphasis on readability and learning. Instead of aiming to be a production runtime, it serves as a reference you can step through to understand how arrays, stacks, queues, linked lists, trees, heaps, graphs, and sorting/searching routines actually work. The implementations favor clarity over micro-optimizations, making them approachable for learners who are new to algorithmic thinking...
    Downloads: 0 This Week
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  • 2
    AhoCorasickDoubleArrayTrie

    AhoCorasickDoubleArrayTrie

    An extremely fast implementation of Aho Corasick algorithm

    ...This makes it a strong fit for tasks like content filtering, entity/term spotting, dictionary-based annotation, or high-throughput log/text processing. In short, it’s a specialized, speed-focused library for industrial-strength multi-keyword matching in Java.
    Downloads: 0 This Week
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  • 3
    STXXL is an implementation of the C++ standard template library STL for external memory (out-of-core) computations, containers, and algorithms that can process huge volumes of data that only fit on disks.
    Downloads: 11 This Week
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  • 4
    pyhanlp

    pyhanlp

    Chinese participle

    pyhanlp is a Python interface for HanLP (Han Language Processing) that lets you use a mature Java-based NLP toolkit from Python workflows without rebuilding the underlying algorithms. It is commonly used for Chinese-language NLP tasks where you want production-grade tokenization and linguistic analysis, but still want the convenience of Python scripting. The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into...
    Downloads: 0 This Week
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  • 5
    The Edge Machine Learning library

    The Edge Machine Learning library

    Machine learning algorithms for edge devices

    Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.These algorithms can train models for classical supervised learning problems with memory requirements that are...
    Downloads: 0 This Week
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  • 6
    New Terrain and 3D Map System

    New Terrain and 3D Map System

    a very lightweight advanced terrain-rendering and 3D map rendering sys

    A very lightweight advanced terrain-rendering and 3D map rendering system. Minimal dependencies: OpenGL, SDL. It's distrib in 2-3 separate modules: 1. the C++ implementation of the terrain- and/or surface- rendering Algorithms I have developed: both a multithread and a non-multithread variant is relaeased. 2. Seme as at point 1. , but with a road-network rendering and collision-detection module I wrote before. It also adds some trees at the top of the terrain. (multitread vesion not...
    Downloads: 0 This Week
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