Open Source Windows Libraries
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Libraries for Windows
View 55 business solutionsBrowse free open source Libraries and projects for Windows below. Use the toggles on the left to filter open source Libraries by OS, license, language, programming language, and project status.
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Auth0 B2B Essentials: SSO, MFA, and RBAC Built InAuth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
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Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Awesome production machine learning
Curated list of awesome open source libraries
This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning. Open-source frameworks, tutorials, and articles curated by machine learning professionals. Open-source bias audit toolkits for data scientists, machine learning researchers, and policymakers to audit machine learning models for discrimination and bias, and to make informed and equitable decisions around developing and deploying predictive risk-assessment tools. -
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jpeg2pdf
Create PDF from JPEG scans and photos
Cross-platform command-line tool for creation of PDF documents from scans/photos of pages in JPEG (.jpg) format and the lightest weight ANSI C library to put multiple JPEG files into one PDF file. You can add handwritten comments to PDF scans (over original images) with xournal: http://xournal.sourceforge.net/ It supports graphics tablets and saves comments to PDFs as vector data. -
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Lucid
A collection of infrastructure and tools for research
Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. You can run the notebooks on your local machine, too. Clone the repository and find them in the notebooks subfolder. You will need to run a local instance of the Jupyter notebook environment to execute them. Feature visualization answers questions about what a network, or parts of a network, are looking for by generating examples. -
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TX Library
TX Library is a tiny graphics library for Win32 written in C++.
TX Library is a tiny graphics library for Win32 written in C++. It is a small sandbox for the very beginners to help them to learn basic programming principles. The documentation is currently in Russian. More info here: http://storage.ded32.net.ru/Lib/TX/TXUpdate/Doc/HTML.ru, http://ded32.net.ru/news/2011-04-03-58, http://ded32.net.ru. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Best-of Python
A ranked list of awesome Python open-source libraries
This curated list contains 390 awesome open-source projects with a total of 1.4M stars grouped into 28 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! Ranked list of awesome python libraries for web development. Correctly generate plurals, ordinals, indefinite articles; convert numbers. Libraries for loading, collecting, and extracting data from a variety of data sources and formats. Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
" Deep Learning " is the only comprehensive book in the field of deep learning. The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc. -
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SigPack
SigPack - A signal processing library using Armadillo
SigPack is a C++ signal processing library using the Armadillo library as a base. The API will be familiar for those who has used IT++ and Octave/Matlab. -
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Hacker Laws
Laws, theories, principles and patterns useful to developers
Laws, Theories, Principles and Patterns that developers will find useful. There are lots of laws which people discuss when talking about development. This repository is a reference and overview of some of the most common ones. Principles and laws to follow such as: If a program is made up of two parts, part A, which must be executed by a single processor, and part B, which can be parallelised, then we see that adding multiple processors to the system executing the program can only have a limited benefit. It can potentially greatly improve the speed of part B - but the speed of part A will remain unchanged. Also, theories like The Broken Windows Theory, which suggests that visible signs of crime (or lack of care of an environment) lead to further and more serious crimes (or further deterioration of the environment). Conway's Law suggests that the technical boundaries of a system will reflect the structure of the organisation. These among others, are featured in this project. -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. Stanza is built with highly accurate neural network components that also enable efficient training and evaluation with your own annotated data. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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JChart2D
jchart2d is a real-time charting library written in java.
JChart2D is a easy to use component for displaying two- dimensional traces in a coordinate system written in Java. It supports real-time (animated) charting, custom trace rendering, Multithreading, viewports, automatic scaling and labels. Former UI controls (right click context menu, file menu) have been ported to the subproject jchart2d-uimenu (https://sourceforge.net/projects/jchart2d-uimenu.jchart2d.p/) for the benefit of having no dependencies to 3rd party libraries. -
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Do you want a neural network OO class? With documentation? Do not go further... You found it! you have here a complete library of different neural network in an OO encapsulation. Starting from adaline, back propagation, Kohonen
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AI Search Agent Framework
Java Framework for Artificial Intelligence Search Agents algorithms
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ATFinder
Configuration finder by AT commands with auto-configure options
Bluetooth module configuration finder by AT commands with auto-configure options for Arduino -
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ATFinder (lib)
BT configuration by AT commands for Arduino (lib)
Bluetooth module configuration finder by AT commands with auto-configure options for Arduino. How to install a library: https://www.arduino.cc/en/Guide/Libraries -
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Azure Data SQL Samples
Official Microsoft repository containing code samples for SQL Server
This GitHub repository contains code samples that demonstrate how to use Microsoft's Azure Data products including SQL Server, Azure SQL Database, Azure Synapse, and Azure SQL Edge. Each sample includes a README file that explains how to run and use the sample. Note that certain features like In-Memory OLTP are edition specific for SQL Server and would be possible to implement if the edition which supports that feature is being used to run the sample. Releases allow you to conveniently download sample databases or applications without the need to build them from source code. Wide World Importers sample database v1.0 is the main sample for SQL Server 2016 and Azure SQL Database. It contains both an OLTP and an OLAP database. In-Memory OLTP Performance Demo v1.0 illustrates the performance benefits of the In-Memory OLTP technology built into SQL Server and Azure SQL Database. IoT Smart Grid sample v1.0 illustrates how SQL Server can be leveraged to ingest data from IoT devices. -
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Seeds is a project which implements Data structure and Algorithms! We aim for speed, flexible and the easy to use!
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Binarytree
Python library for studying Binary Trees
Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. Traverse trees using different algorithms. -
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The BioloidNativeInterface is a C++ library to control bioloid/dynamixel modules including AX12, AXS1. It provides a parser for the bioloid protocoll and methods to read/write packets.
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CSharp MARC
Full featured editor for reading and manipulating MARC Records
*** THIS PROJECT HAS MOVED TO GITHUB *** https://github.com/frozen-solid/CSharp_MARC/ ********************************************************** C# MARC: C# class structures for reading and manipulating Library of Congress MARC records using the MARC21 standard. Based upon the PHP Pear package File_MARC (http://pear.php.net/package/File_MARC) by Dan Scott. C# MARC Editor: A full featured SQLite based editor for quickly modifying MARC records and exporting them to MARC21 or MARCXML. -
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Calcex Math Parser
Mathematical expression parser and evaluator for .NET
Moved to https://github.com/alxnull/calcex Calcex is a simple math parser for .NET to evaluate mathematical expressions which is developed in C#. It supports many common mathematical operations and functions and allows the user to add custom functions and variables. It is possible to evaluate double or decimal values for high precision. Calcex also includes functions for converting numbers from decimal to binary or other bases. The project includes a simple calculator and decimal-binary converter to show the functions of Calcex. -
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Canvas++
Single-header graphics library to teach C++
Canvas++ is a very simple graphics library contained in single header file. It's purpose is to make teaching of C++ more colorful and funny for kids and students. The main idea is to wrap windows API calls into simple interface. You can start drawing next after "Hello world" example - just declare Window variable and call method draw() to start drawing. -
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Imlementation of SOM (Self organizing networks) a neural network for IBM Cell Broadband Engine Architecture.
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DIG
A library for graph deep learning research
The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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Major looseless compression algorithms library and documentation. First project: Arithmetic, Huffman, LZ77, LZ78, LZW, RLE. Second project reimplements Deflate. Documentation explains major Entropy Compression Methods.
