A group of neural-network libraries for functional and mainstream languages!
Choose a programming language:
The implementation is based on lazy list. The information flows smoothly. Everything is obtained at a single pass.
You can specify the activation function and the weight distribution for the neurons of each layer. If this is not enough, edit the json of a network to be exactly what you have in mind.
It offers visualizations
Get an overview of a neural network by taking a brief look at its svg drawing.
Data preprocessing is simple
By annotating the discrete and continuous attributes, you can create a preprocessor that encodes and decodes the datapoints.
Works for huge datasets
The functions that process big volumes of data, have an Iterable/Stream as argument. RAM should not get full!
It’s well tested
Every function is tested for every language. Take a look at the test projects.
It’s compatible across languages