Search Results for "c programming" - Page 5
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Showing 108 open source projects for "c programming"
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An open-source library to support Stanford's course 'Programming Abstractions', CS106B/X. Written initially for Linux, but porting to Windows/MinGW is planned.
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APTools (Accelerate Programming Tools) is a .NET libraries that aim to provide common needed objects and functions and therefore accelerate programming. Its brings immutable collections, parameter validation, design patterns interfaces and more.
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OpenGI is a platform-independent C-library for parameterizing triangular meshes and creating Geometry Images from this parameterization.
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LIEL (Language Independent Extension Library) is a language-agnostic library containing solutions to various programming problems and extending the capabilities of existing frameworks and code libraries.
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LSGTL means LLX’s Static Graph Template Library which is a light-weighted header-only template library developed mainly for static graph analysis. LSGTL is expected to be used in laboratories for research purposes mostly.
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Prog is a lightweight, high-level, general-purpose, interpretable, compilable, strongly typed language that balances pragmatism, legibility, and versatility. Types are first-class objects and evaluation is considered a side-effect of type conversion.
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LibThreadPool
Library for easy multithreading programming
The ThreadPool library is a simple and efficient way to manage multiple tasks in a program. It allows you to run several tasks at the same time using a pool of worker threads. The entire implementation is provided in one single header file, making it extremely portable and hassle-free to integrate into your project. Whether you are building a small project or a larger application, this library offers the necessary tools to efficiently handle multi-threading with minimal... -
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DBNL
Dynamic Bayesian Network Library
DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machine learning algorithms. It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure. It can handle highly non-linear dependencies between multivariate random variables. The particle based inference can answer arbitrary...
