Shypd.aiThe largest open index of AI toolsMGL is a Common Lisp machine learning library focusing on neural networks, Boltzmann machines, and Gaussian processes. It offers BLAS and CUDA support for high performance.
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MGL is a powerful machine learning library specifically designed for Common Lisp, developed by Gábor Melis. It concentrates primarily on various forms of neural networks, including Boltzmann machines, feed-forward, and recurrent backpropagation networks. Built on top of MGL-MAT, it leverages BLAS and CUDA for enhanced performance, making it suitable for computationally intensive tasks. While its focus is on power and performance rather than ease of use, it provides extensive functionalities for data resampling, cross-validation, gradient-based optimization, and differentiable functions. The library includes a modular code organization with dedicated packages for different tasks, and it can fall back to BLAS and Lisp code if a suitable GPU or CUDA SDK is not available.
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