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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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PlatEMO
Evolutionary multi-objective optimization platform
Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)... -
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Flatbush
A very fast static spatial index for 2D points and rectangles in JS
A really fast static spatial index for 2D points and rectangles in JavaScript. An efficient implementation of the packed Hilbert R-tree algorithm. Enables fast spatial queries on a very large number of objects (e.g. millions), which is very useful in maps, data visualizations and computational geometry algorithms. -
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bild
Image processing algorithms in pure Go
A collection of parallel image processing algorithms in pure Go. The aim of this project is simplicity in use and development over absolute high performance, but most algorithms are designed to be efficient and make use of parallelism when available. It uses packages from the standard library whenever possible to reduce dependency use and development abstractions. All operations return image types from the standard library. Package convolution provides the functionality to create and apply a... -
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C# Algorithms
Plug-and-play class-library project of standard data structures
A plug-and-play class-library project of standard Data Structures and Algorithms, written in C#. It contains 75+ Data Structures and Algorithms, designed as Object-Oriented isolated components. Even though this project started for educational purposes, the implemented Data Structures and Algorithms are standard, efficient, stable and tested. This is a C#.NET solution-project, and it contains three subprojects. Algorithms, a class library project which contains the Algorithms implementations.... -
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Evolutionary.jl
Evolutionary & genetic algorithms for Julia
A Julia package for evolutionary & genetic algorithms. The package can be installed with the Julia package manager. -
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Arduino FOC
Arduino FOC for BLDC and Stepper motors
We live in very exciting times 😃! BLDC motors are entering the hobby community more and more and many great projects have already emerged leveraging their far superior dynamics and power capabilities. BLDC motors have numerous advantages over regular DC motors but they have one big disadvantage, the complexity of control. Even though it has become relatively easy to design and manufacture PCBs and create our own hardware solutions for driving BLDC motors the proper low-cost solutions are yet... -
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Hello Algorithm
Animated illustrations, one-click data structure
Animated illustrations, one-click data structure and algorithm tutorials. This project aims to create an open source, free, novice-friendly introductory tutorial on data structures and algorithms. The whole book uses animated illustrations, the content is clear and easy to understand, and the learning curve is smooth, guiding beginners to explore the knowledge map of data structures and algorithms. The source code can be run with one click, helping readers improve their programming skills... -
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leetcode-editor
Do Leetcode exercises in IDE
Do Leetcode exercises in IDE, support leetcode.com and leetcode-cn.com, to meet the basic needs of doing exercises.Support theoretically: IntelliJ IDEA PhpStorm WebStorm PyCharm RubyMine AppCode CLion GoLand DataGrip Rider MPS Android Studio. The login accounts of the two websites are not interoperable and the corresponding users need to be configured when switching websites. You can also refresh and load questions if you are not logged in, but you cannot submit it. Input the content and... -
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NutsDB
A simple, fast, embeddable, persistent key/value store written in Go
A simple, fast, embeddable, persistent key/value store written in pure Go. It supports fully serializable transactions and many data structures such as list, set, sorted set. It supports fully serializable transactions and many data structures such as list、set、sorted set. All operations happen inside a Tx. Tx represents a transaction, which can be read-only or read-write. Read-only transactions can read values for a given bucket and a given key or iterate over a set of key-value pairs.... -
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tsfresh
Automatic extraction of relevant features from time series
tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python.... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural... -
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supercluster
A very fast geospatial point clustering library for browsers and Node
A very fast JavaScript library for geospatial point clustering for browsers and Node. supercluster supports property aggregation with the following two options. Map, a function that returns cluster properties corresponding to a single point. Reduce, a reduce function that merges properties of two clusters into one. -
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TBOX
A glib-like multi-platform c library
...The project focuses on making C development easier and provides many modules (.e.g stream, coroutine, regex, container, algorithm ...), so that any developer can quickly pick it up and enjoy the productivity boost when developing in C language. It supports the following platforms: Windows, Macosx, Linux, Android, iOS, BSD and etc. Supports file, data, http and socket source. Supports the stream filter for gzip, charset. etc. Implements stream transfer. Implements the static buffer stream for parsing data. Supports coroutine and implements asynchronous operation. The coroutine library. Provides high-performance coroutine switch. ... -
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JCTools
Java Concurrency Tools for the JVM
Java Concurrency Tools for the JVM. This project aims to offer some concurrent data structures currently missing from the JDK. There’s more to come and contributions/suggestions are most welcome. JCTools has enjoyed support from the community and contributions in the form of issues/tests/documentation/code have helped it grow. JCTools offers excellent performance at a reasonable price (FREE! under the Apache 2.0 License). It’s stable and in use by such distinguished frameworks as Netty,... -
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Delaunator
Fast JavaScript library for Delaunay triangulation of 2D points
Delaunator is a fast library for Delaunay triangulation. It takes as input a set of points. The triangulation is represented as compact arrays of integers. It’s less convenient than other representations but is the reason the library is fast. After constructing a delaunay = Delaunator.from(points) object, it will have a triangles array and a halfedges array, both indexed by half-edge id. What’s a half-edge? A triangle edge may be shared with another triangle. Instead of thinking about each... -
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DeepSpec
A full-stack codebase for training and evaluating speculative decoding
DeepSpec is a full-stack codebase for training and evaluating draft models used in speculative decoding. It provides the components needed to prepare data, train draft models, and measure acceptance behavior against target models. The workflow starts with data preparation, including prompt download, target answer regeneration, and target cache construction. It then trains a draft model using configuration files for different algorithms and target model setups. The evaluation pipeline... -
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Machine Learning Octave
MatLab/Octave examples of popular machine learning algorithms
This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on... -
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The Algorithms Python
All Algorithms implemented in Python
The Algorithms-Python project is a comprehensive collection of Python implementations for a wide range of algorithms and data structures. It serves primarily as an educational resource for learners and developers who want to understand how algorithms work under the hood. Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting,... -
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EASTL
EASTL, Electronic Arts Standard Template Library
EASTL stands for Electronic Arts Standard Template Library. It is a C++ template library of containers, algorithms, and iterators useful for runtime and tool development across multiple platforms. It is a fairly extensive and robust implementation of such a library and has an emphasis on high performance above all other considerations. If you are familiar with the C++ STL or have worked with other templated container/algorithm libraries, you probably don't need to read this. If you have no... -
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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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GraphEmbedding
Implementation and experiments of graph embedding algorithms
GraphEmbedding is an open-source Python project for implementing and experimenting with graph embedding algorithms. It follows a simple “graph in, embedding out” design. The library uses NetworkX graphs as input and produces vector representations for graph nodes. It includes implementations of DeepWalk, LINE, Node2Vec, SDNE, and Struc2Vec. Users can configure walks, embedding dimensions, training windows, epochs, and other model-specific parameters. Example scripts demonstrate how to train... -
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ai-notebooks
Some ipython notebooks implementing AI algorithms
ai-notebooks is a collection of Jupyter notebooks that implements machine-learning and artificial-intelligence ideas in compact, inspectable experiments. The examples are written primarily in Python and use frameworks including TensorFlow, PyTorch, Keras, JAX, and tinygrad. Projects explore problems such as MNIST learning, GANs, VAEs, model compression, and knowledge distillation. Other notebooks examine reinforcement learning through PPO, SAC, TD3, VPG, and MuZero experiments. Transformer,... -
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go-algorithms
Algorithms and data structures for golang
go-algorithms is an open-source educational repository that provides implementations of common algorithms and data structures written in the Go programming language. The project is designed primarily as a learning resource to help developers understand how fundamental computer science concepts can be implemented idiomatically in Go. It includes a wide range of classic sorting, searching, and numerical algorithms alongside basic collection structures such as stacks, queues, linked lists, and...
