An artificial intelligence technique designed to mimic the way the human brain functions. The technique passes information across multiple nodes, or interconnected algorithms, arranged in layers. Neural networks are often called “black boxes” because they generate results that cannot be easily explained.
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Deep learning is a term for technologies that use artificial neural network (ANNs) algorithms. Experts consider deep learning and ANNs to be the same thing and use the terms interchangeably. Just like neural networks in brains, ANNs have neurons (nodes) interconnected by synapses (links). Each node receives data, performs an operation, and passes the new data to another node via a link. The links contain weights or biases that influence the next node’s operation. To illustrate the roles of nodes and links, imagine a company that wants to predict whether a customer will renew a subscription based on two predictors, gender and age. The company’s neural network has two input nodes--one for each predictor--connected via separate links to one output node. Gender and age values are fed into the input nodes. Those values are multiplied by preset weights in the links. If age happens to be a better predictor than gender, then the link that sends age data will have a higher weight.
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