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This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.
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. Bindings to more than 15 programming languages are available. An easy to read...
Neural Mesh is a purely PHP, fast, easy Neural Network Manager, Administrator and Framework. It allows you to integrate Artificial Intelligence into your applications, quickly and easily, no matter what your experience.
Thank you for your interest in Speedy Composer. Speedy Composer is an automated application for composing melodies for Speedy Net members. We recently made changes to the source code of Speedy Net, and converted it into the Python language and Django framework. Since Speedy Composer was originally written in PHP, it is not adapted to work with Speedy Net in its current form. So unfortunately we were forced to temporarily close the app Speedy Composer. But don't worry, we kept backups of all...
AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
PHPNN Is an open source, GPL licensed, PHP class library for the easy creation and manipulation of Neural Network based artificial intelligence. This library is intended for use in experimentation, games, quality control, or any other purpose.
Neural network libraries in many different languages compatible with each other, such that neural networks can be trained on one platform and utilised on another.