Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. PHP, C++, .NET, Ada, Python, Delphi, Octave, Ruby, Prolog Pure Data and Mathematica bindings are available. A reference manual accompanies the library with examples and recommendations on how to use the library. A graphical user interface is also available for the library.
J. Tritscher, D. Schlör, F. Gwinner, A. Krause, и A. Hotho. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2022, Communications in Computer and Information Science (1753):
79-96(2022)
J. Tritscher, D. Schlör, F. Gwinner, A. Krause, и A. Hotho. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2022, Communications in Computer and Information Science (1753):
79-96(2022)
G. Gao, E. Choi, Y. Choi, и L. Zettlemoyer. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, стр. 607--613. Brussels, Belgium, Association for Computational Linguistics, (2018)