We’ve open sourced it on GitHub with the hope that it can make neural networks a little more accessible and easier to learn. You’re free to use it in any way that follows our Apache License.

It’s a technique for building a computer program that learns from data, based very loosely on how brains work. Software “neurons” are connected together, allowing them to send messages to each other.

The simulator will help you understand how artificial neural network works. The network is trained using backpropagation algorithm, and the goal of the training is to learn the XOR function.

ENNUI helps people learn about deep learning by building, training, and visualizing deep neural networks on the browser. It has an easy to use drag-and-drop interface.

6DNet - A Neural Network Simulator 6DNet is an educational game which is useful for und erstanding how neural networks and backpropogation work.

Watch neural networks come to life with real-time, interactive visualizations. Learn complex AI concepts through hands-on experimentation. Experience instant feedback as you modify network parameters. …

NEST is a simulator for spiking neural network models that focuses on the dynamics, size and structure of neural systems rather than on the exact morphology of individual neurons.

This simulator visualizes the training process of a basic Neural Network. It is composed of four layers: an input layer, two hidden layers, and an output layer.

Nengo is a graphical and scripting based Python package for simulating large-scale neural networks.

Instead of seeing a neural network as a differentiable function approximator, the corporation metaphor suggests seeing a neural network as a bunch of online learning algorithms, stacked on top of each …