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mlpack is a free, open-source and header-only software library for machine learning and artificial intelligence written in C++, built on top of the Armadillo library and the ensmallen numerical optimization library. [3] mlpack has an emphasis on scalability, speed, and ease-of-use.
OpenNN (Open Neural Networks Library) is a software library written in the C++ programming language which implements neural networks, a main area of deep learning research. [1] The library is open-source , licensed under the GNU Lesser General Public License .
C++ is a compiled language that can interact with low-level hardware. 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 ...
Keras, a high level open-source software library for machine learning (works on top of other libraries). [81] Microsoft Cognitive Toolkit (previously known as CNTK), an open source toolkit for building artificial neural networks. [82] OpenNN, a comprehensive C++ library implementing neural networks. [83]
On July 1, 2020 a new fork version 5.50 of Dev-C++ was sponsored and released by Embarcadero featuring a code upgrade to Delphi 10.4. On October 12, 2020 a new fork version 6.0 of Dev-C++ was sponsored and released by Embarcadero with a more recent GCC 9.2.0 compiler with C++11 and partial C++20 support, new high DPI support, UTF8 file support ...
The world of artificial intelligence (AI) has been rapidly expanding, infiltrating various fields, industries and professions. ... 6 Best Free AI Programs for Beginners To Save and Make Money ...
Crypto++ (also known as CryptoPP, libcrypto++, and libcryptopp) is a free and open-source C++ class library of cryptographic algorithms and schemes written by Wei Dai. Crypto++ has been widely used in academia, student projects, open-source, and non-commercial projects, as well as businesses. [ 1 ]
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".