How BrainMaker Neural Networks work Neural networks are named after the cells in the human brain that perform intelligent operations. The brain is made up of billions of neuron cells. Neural networks are formed from hundreds or thousands of simulated neurons connected together in much the same way as the brain's neurons. Just like people, neural networks learn from experience, not from programming.
Neural networks are good at pattern recognition, generalization, and trend prediction.
They are fast, tolerant of imperfect data, and do not need formulas or rules. Neural networks are trained by repeatedly presenting examples to the network. Your network tries to learn each of your examples in turn, calculating its output based on the inputs you provided. If the network output doesn't match the target output, BrainMaker corrects the network by changing its internal connections. Once the network is trained and tested, you can give it new input information, and it will produce a prediction.