Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 2
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Showing 149 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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javascript-algorithms
JavaScript implementations of computer science algorithms
...Because algorithms are implemented in a language (JavaScript) many developers use daily, the repo becomes especially useful for students, interview-preparation candidates, or anyone wanting to learn algorithmic thinking without switching languages. The code tends to be readable, structured, and adapted to JavaScript idioms, making it easier to follow for JS developers. -
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Gait Tracking With x-IMU
Foot tracking algorithm demonstrated in Seb Madgwick's 3D Tracking
This repository provides the source code for a foot-tracking algorithm using an inertial measurement unit (IMU) attached to the foot, as demonstrated in Seb Madgwick’s “3D Tracking with IMU” video (March 2011). The method performs dead reckoning to integrate foot motion and corrects for drift at each foot strike (when the foot touches the ground) to reset error accumulation. -
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ringBufU
Ring-Buffer library in C, includes support of multithreading
...Some features are globally choosable on compile-time (e.g. switch multithread support off completely to have faster access). Note: User Interface is for Test and Tutor Code only. -
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...Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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Data management solutions for confident marketingVerify, deduplicate, manipulate, and assign records automatically to keep your CRM data accurate, complete, and ready for business.
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Thrust
The C++ parallel algorithms library
Thrust is the C++ parallel algorithms library which inspired the introduction of parallel algorithms to the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. It builds on top of established parallel programming frameworks (such as CUDA, TBB, and OpenMP). It also provides a number of general-purpose facilities similar to those found in the C++ Standard Library. The NVIDIA C++... -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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VS Code LeetCode
Solve LeetCode problems in VS Code
...Directly click on the problem or right-click the problem in the LeetCode Explorer and select Preview Problem to see the problem description. Select Show Problem to directly open the file with the problem description. The extension supports 5 editor shortcuts (aka Code Lens). To manage your LeetCode sessions, just clicking the LeetCode: *** at the bottom of the status bar. You can switch between sessions or create, delete a session. -
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D-List
An extensive list subsystem, written in C
...It also provides for an expansive set of user functions that can be added to lists and called automatically, to efficiently implement a broad range of services using the list primitives as underlying technology. It was written primarily for accuracy and speed, and provides extensive debugging support for easy code development. -
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Real-ESRGAN ncnn Vulkan
NCNN implementation of Real-ESRGAN
Real-ESRGAN ncnn Vulkan is an optimized, cross-platform implementation of Real-ESRGAN using the ncnn neural network inference engine and Vulkan for hardware acceleration. Unlike the standard PyTorch-based Real-ESRGAN code, this variant is written in C/C++ and designed to run efficiently on many platforms (including Windows, Linux, and possibly Android) without requiring heavy frameworks like CUDA or Python. It provides command-line tools for upscaling images with selected models, allowing users to specify input/output paths, scaling factors, tile sizes, and model names from a compressed model set, which is particularly helpful for larger images or automated workflows. ... -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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LeetCode Python
LeetCode Solutions: A Record of My Problem Solving Journey
This repository is a comprehensive personal journal of LeetCode problem-solving journey. It includes detailed solutions with code, algorithm insights, data structure summaries, Anki flashcards, daily challenge logs, and future planning sections. -
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CountBitsSet
minimal benchmark code for Counting Set Bits (ones) in an Integer
...Also this shows nicely how different a human brain compatible solution is to a binary machine optimal solution :-) In the meantime I added other Algorithms beside countbisset (hamming weight): ceil(log2()) + floor(log2()), bitreverse, ... I also recommand to try the code with different compilers and / or plattforms. PS: see result.txt in Code, to see various runs with different compilers and compiler switches -
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go-algorithms
Algorithms and data structures for golang
...It includes a wide range of classic sorting, searching, and numerical algorithms alongside basic collection structures such as stacks, queues, linked lists, and binary trees. The repository is organized into clear directories by topic, making it easy for learners to explore specific categories of algorithms. Because the code focuses on clarity over heavy abstraction, it is especially useful for students and developers studying algorithmic fundamentals. Overall, go-algorithms serves as a practical reference and study companion for Go programmers building a strong foundation in data structures and algorithm design. -
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NTU RGB-D
Info and sample codes for "NTU RGB+D Action Recognition Dataset"
The “NTU RGB+D” repository provides access to a large-scale dataset for human action recognition (and its extension, NTU RGB+D 120). The dataset includes multiple modalities (RGB video, depth sequences, infrared video, 3D skeletal joint data) captured with multiple Kinect v2 cameras simultaneously. The repository also contains MATLAB / Python demo scripts for loading, visualizing, and processing skeleton data, mapping between modalities, and handling dataset structure. Multi-modal action... -
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Arduino
Open-source electronics platform
...Arduino is the first widespread Open Source Hardware project and was set up to build a community that could help spread the use of the tool and benefit from contributions from hundreds of people who helped debug the code, write examples, create tutorials, etc. -
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TA-Lib.git: Technical Analysis Library
Mirror of the TA-Lib project using a Git repository
This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project. -
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code-nav
Professional programming navigation
Programming Navigation is not just a website, but a complete ecology with the goal of "helping everyone discover high-quality programming resources and improve learning efficiency". It contains multiple sub-projects, and the technology stack includes React, Java SpringBoot, Tencent Cloud Development, etc., all of which are open source for everyone to learn, so that you can easily develop beautiful information navigation websites! Most of the programming navigation websites are in disrepair... -
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lpsolve
Mixed Integer Linear Programming (MILP) solver.
Mixed Integer Linear Programming (MILP) solver lp_solve solves pure linear, (mixed) integer/binary, semi-cont and special ordered sets (SOS) models.lp_solve is written in ANSI C and can be compiled on many different platforms like Linux and WINDOWS This project is moved to github: https://lp-solve.github.io/ -
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Kalman and Bayesian Filters in Python
Kalman Filter book using Jupyter Notebook
...Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions. Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. What better way to learn? This book teaches you how to solve all sorts of filtering problems. Use many different algorithms, all based on Bayesian probability. In simple terms Bayesian probability determines what is likely to be true based on past information. ... -
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Supervised Reptile
Code for the paper "On First-Order Meta-Learning Algorithms"
The supervised-reptile repository contains code associated with the paper “On First-Order Meta-Learning Algorithms”, which introduces Reptile, a meta-learning algorithm for learning model parameter initializations that adapt quickly to new tasks. The implementation here is aimed at supervised few-shot learning settings (e.g. Omniglot, Mini-ImageNet), not reinforcement learning, and includes scripts to run training and evaluation for few-shot classification. -
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C-squares
Concise spatial query and representation system (c-squares)
C-squares is an easily implemented method for storage, querying and display of spatial data locations, based on a hierarchical, grid-based representation of the Earth' surface. Source code for encoding, decoding, mapping, etc. is provided via this site. Additional support is available by contacting the system developer, Tony.Rees@marinespecies.org; see also the c-squares home page at http://www.cmar.csiro.au/csquares/ . -
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Programmer's library for random numbers. Also random number generator testing code. Intended for simulation, games and "Monte-Carlo" algorithms.
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MADDPG
Code for the MADDPG algorithm from a paper
...The code is built on top of TensorFlow and integrates with the Multiagent Particle Environments (MPE) for benchmarking. Researchers can use it to reproduce the experiments presented in the paper, which demonstrate how agents learn behaviors such as coordination, competition, and communication. Although archived, MADDPG remains a widely cited baseline in multi-agent reinforcement learning research and has inspired further algorithmic developments. -
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FuzzyWuzzy
Fuzzy string matching in Python
...When we scour the web to find tickets for sale, mostly those tickets are identified by a title, date, time, and venue. We’ve built up a library of “fuzzy” string matching routines to help us along. And good news! We’re open sourcing it. The library is called “Fuzzywuzzy”, the code is pure python, and it depends only on the (excellent) difflib python library. -
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EN: Code created to show how is done the calculation of a CRC. It includes many different CRCs to choose from. This software was created to help people understand how is the CRC calculated and be able to see it in a practical way, it is also available to copy and use it for your own project. I hope it helps you. ES: Código creado para mostrar como se realiza el cálculo de un CRC.
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PRMLT
Matlab code of machine learning algorithms in book PRML
...This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry.
