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Showing 15 open source projects for "quick"
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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... -
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Rubix ML
A high-level machine learning and deep learning library for PHP
...We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. Train models in a fraction of the time by installing the optional Tensor extension powered by C. ... -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. For students preparing for technical interviews, self-learners brushing up on... -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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VR Paged List for C# and more
VR Paged List for C# and more
a collection of Vincent Radio {Adrix.NT} C# sources & build projects includes - Paged Lists & Iterators Library for C# - Multi Dimensional Array Library for C# - MDArray List Manager Library for C# - Adjacency (List | Matrix) Direct Graph Libs for C# - Range Check functions - VRMosaic (WinForms) - with Auto Resolver also includes - Source Files - Visual Studio Build Projects - Test Applics have fun adrixnt@hotmail.it -
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javascript-algorithms
JavaScript implementations of computer science algorithms
javascript-algorithms is a repository that implements a comprehensive collection of classic data structures and algorithmic solutions in JavaScript — including sorting, searching, graph algorithms, dynamic programming, and more. It serves as a learning and reference resource for developers wanting to understand how standard algorithms can be expressed in JavaScript, bridging the gap between theoretical algorithm knowledge and practical implementation usable in web or Node.js contexts.... -
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Machine Learning Cheat Sheet
Classical equations and diagrams in machine learning
...It includes summaries of supervised and unsupervised learning methods, model evaluation metrics (accuracy, precision, recall, ROC/AUC), overfitting/underfitting, regularization (L1/L2), cross-validation, feature engineering techniques, and perhaps tips for hyperparameter tuning. Each section is presented concisely, often with diagrams, formula snippets, and short explanatory notes to serve as quick reference for students, practitioners, or interview prep. The repository is ideal for those who want a compact, at-a-glance reminder of ML fundamentals without diving back into textbooks. Because the cheat sheet is meant to be portable and broadly useful, it is format-friendly (often in Markdown, PDF, or image formats) and easy to include in learning workflow or slides. -
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Code Catalog in Python
Algorithms and data structures for review for coding interview
...It favors clarity over micro-optimizations so learners can grasp the idea before worrying about edge performance. Over time it becomes a personal cookbook of solutions you can remix across projects. This approach is especially helpful when you need a quick refresher on a technique you haven’t used in a while. -
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Java Sorting
A program to benchmark 5 different sorting algorithms.
This program benchmarks the following sorting algorithms implemented in Java: Quick Sort, Heap Sort, Merge Sort, Selection Sort, and Bubble Sort. A command line GUI was created to facilitate all your benchmark needs. -
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3 Generic C Sorting algorithms
3 generic sorting algorithms written in C
Generic merge sort, quick sort and insertion sort implementations written in C programming language. -
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Simple Fast Dictionary
Simple, small and fast dictionary lib on C
The library does quick search of dictionary words in arbitrary input strings. Known problems are known. :) See appropriate section in documentation. Also, only ASCII words and strings for now. -
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Java implementation of the most commonly used algorithms for exact string matching, where the pattern is given first.
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Sinalgo is a simulation framework for testing and validating network algorithms. It allows for quick prototyping and verification in freely customizable network settings. It is mainly suited for packet-oriented wireless networks.
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QuickMP (Quick Multi-Processing) is a simple cross-platform C++ API for generating parallel for loops in shared-memory programs, similar to OpenMP. It provides automatic scalable performance based on the number of available processors.
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Multi-platform regular expression (regex) creation. Highlights regex matches, and regex groups for quick regular expression creation. Save/load regular expression sessions. Create robust regex patterns on any major platform. Supports PCRE and wxRegEx.
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