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This is a computer vision and artificial intelligence library. [14] [15] It implements a number of image processing algorithms and filters. It is released under the LGPLv3 and partly GPLv3 license. Majority of the library is written in C# and thus cross-platform. [citation needed] Functionality of AForge.NET has been extended by the Accord.NET ...
ML.NET is a free software machine learning library for the C# and F# programming languages. [4] [5] [6] It also supports Python models when used together with NimbusML.The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks. [7]
AForge.NET is a computer vision and artificial intelligence library originally developed by Andrew Kirillov for the .NET Framework. [2]The source code and binaries of the project are available under the terms of the Lesser GPL and the GPL (GNU General Public License).
In the context of AI, it is particularly used for embedded systems and robotics. Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6]
C#, C++ C#, F# Yes Apache MXNet: Apache Software Foundation 2015 Apache 2.0: Yes Linux, macOS, Windows, [39] [40] AWS, Android, [41] iOS, JavaScript [42] Small C++ core library C++, Python, Julia, MATLAB, JavaScript, Go, R, Scala, Perl, Clojure: Yes No Yes No Yes [43] Yes [44] Yes Yes Yes Yes [45] No Neural Designer: Artelnics 2014 Proprietary ...
It works on Linux, Windows, macOS, and is available in Python, [8] R, [9] and models built using CatBoost can be used for predictions in C++, Java, [10] C#, Rust, Core ML, ONNX, and PMML. The source code is licensed under Apache License and available on GitHub. [6] InfoWorld magazine awarded the library "The best machine learning tools" in 2017.
IMSL Numerical Libraries are libraries of numerical analysis functionality implemented in standard programming languages like C, Java, C# .NET, Fortran, and Python. The NAG Library is a collection of mathematical and statistical routines for multiple programming languages (C, C++, Fortran, Visual Basic, Java, Python and C#) and packages (MATLAB ...
The library has been used for research in image recognition, machine learning, biology, genetics, aerospace engineering, environmental sciences and artificial intelligence. Notable publications that cite FANN include: Papa, J. P. (2009). "Supervised pattern classification based on optimum-path forest".