Open Source Libraries
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View 52 business solutionsBrowse free open source Libraries and projects for Mac and Linux 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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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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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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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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RELATED - REmotes LAboraTories extenED
Java Framework for developing of remote/virtual laboratories
RELATED framework proposes a structured methodology of remote/virtual labs development and, also, provides common facilities as user management, booking, basic visualization (trend graphs and direct interaction using interactives variables), data logging and experimental session’s control. In order to get these facilities, an RLAB (Remote LABoratory) system it defined using a formal specification of a virtual or remote laboratory (based on XML and used to structure components for laboratory). The main component is experiment, so students could run these experiments using RELATED facilities as painting data from the laboratory, change any relevant variable or take a look on laboratory structure. In order to integrate a laboratory as an RLAB system, the researchers and lecturers only have to develop local access to equipment using Java technology, using the “module” paradigm. -
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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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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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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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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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Imlementation of SOM (Self organizing networks) a neural network for IBM Cell Broadband Engine Architecture.
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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 questions given the provided evidence and can even cope with multimodal densities. The library supports the most common types of densities and conditional densities, like uniform or normal densities and facilitates user defined density functions. To enable easy use the library is taking account of modern development techniques like policy based design and template programming. All these properties make it applicaple for a wide range of applications. -
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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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A small and simple library for reading and parsing MARC (bibliographic ISO-2709) records quickly. If you need to read and parse MRC files - it is that suits you.
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Frevo
Frevo is probably the simplest tool for evolutionary design
FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations and methods or to connect an external simulation tool. The latest version in development is hosted at https://github.com/smartgrids-aau/Frevo -
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Geospace Analysis Package
MatLab toolbox for magnetospheric and ionospheric science.
A MatLab toolbox with many simple and useful functions for analyzing data from Cluster, Champ and the Swarm missions. Other functions for space plasma physics, magnetospheric and ionospheric research are included. The toolbox is designed to be as simple as possible. Each function can be learned and used individually. See the tutorial in the Files section for a quick introduction. -
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JSentiWordNet
A wrapper for the famous SentiWordNet, a resource for opinion mining
This project aims to provide a wrapper around the SentiWrodnet, a lexical resource for opinion mining. As defined by the authors : SentiWordNet assigns to each synset of WordNet three sentiment scores: positivity, negativity, objectivity. You can find additional information about the creation of SentiWordnet here : http://nmis.isti.cnr.it/sebastiani/Publications/LREC06.pdf sentiWordnet (avilable here : https://drive.google.com/open?id=0B0ChLbwT19XcOVZFdm5wNXA5ODg) is a text file with a specific format that saves a synset on each line. In this project, we aim to provide a wrapper that allows developers to use SentiWordnet without the need to interact directly with the text file. The project allows simple interrogation using a simple GUI and a REST Web service. -
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Kemet API is a Java library which introduces the transcription and transliteration of egyptian hieroglyphs based on the list of Gardiner's signs (middle egyptian). Kemet API is a part of Kemet project - Art and Culture - Archeology - Egypt
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KemetLF is a Java/Swing library + DEMO which defines the Look and Feel of kemet project. This library which introduces the transcription and transliteration of egyptian hieroglyphs based on the list of Gardiner's signs (middle egyptian) - Art and Cu
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Last Java Collection Library
Java library to work with scalar arrays as usual Collections
The package allows to work with scalar arrays as usual collections. The problem with a scalar array Java templates don't support scalar types as generic parameters. Java code working with collection interfaces such as List or Collection is inapplicable for arrays. Some libraries supply methods to work with object array. These methods are generic and built-in types int, boolean, long, short, byte, double, float suffer. The number of scalar type is small and finite. There are realization of Iterable, Iterator, Collection, and List interfaces for each scalar type. Also the library gives such useful methods as contains and indexOf for objects with Iterable interface only. Yeah. There is some stupidness because all implementations differ between each other only types and this code has 100% implicit coupling and duplications. But Java has not left other way. -
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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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Numerikus is an attempt to build a set of numerical libraries written in C/C++, Fortran, Java and C# for single processor and multi-core processors. It wil have from basic functions to Linear Algebra solvers and ODE's and PDE's methods.
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PHPProjectLibrary
A shared, on-line PHP class library tutorial and development project
PHPProjectLibrary.is a tutorial driven PHP class library development project. It seeks to teach PHP class library development by combining the power of Open Source development with the skills of the Open Source community. -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested under GPU and python3. But in theory there shouldn't be too many problems on python2 and CPU. The basic part (the first five chapters) explains the content of PyTorch. This part introduces the main modules in PyTorch and some tools commonly used in deep learning. For this part of the content, Jupyter Notebook is used as a teaching tool here, and readers can modify and run with notebooks and repeat experiments.
