NeuralN is a C++ Neural Network library for Node.js with multiple advantages compared to existing solutions Works with extra large datasets (>1Go allowed by nodejs) and Multi-Threaded training available.
Artificial Neural Network Software
Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)
NeuralN is a C++ Neural Network library for Node.js with multiple advantages compared to existing solutions. It works with extra-large datasets (>1Go allowed by nodejs) and Multi-Threaded training available. With Node.js and the V8, it is not possible to work with large datasets since the maximum allowed memory is around 512MB for 32-bits machines and 1GB for 64-bits machines. When working with datasets of several gigabytes, it quickly becomes difficult to train the network with all the data. NeuralN allows users to use datasets as big as their memory can contain. Working with large datasets increases the performances of the final network, but the learning phase can sometimes take up to several days or even weeks to obtain good results. With the multi-threaded training method of NeuralN, users can significantly reduce the duration of the learning phase, by training their networks simultaneously on different parts of their dataset. The results of each iteration are then combined. NeuralN can return a string representation of the network in order to save and reload it later. It can also return a string representation of each neuron of the network. It allows users to understand which entrance neurons most impacted the final result. Moreover, it can return a json representation of the network and the network’s state but this is not recommended when the network structure gets big. NeuralN features a `visu_state` tool that takes as argument the state of a neural network right after classification and generates an html page rendering the classification state using SVG. The `visu_state` command takes a filename as argument containing the neural network state string as returned by the `get_state` method.
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