This means there are two important decisions to make before we train a artificial neural network: (i) the overall architecture of the system (how input nodes represent given examples, how many hidden ...

The number of hidden layers in a network depends on the complexity of the task. Every node in the neural network goes through a lot of steps. First, it gets data from the input layer or the ...

Artificial neural networks have been applied to problems ... This is usually done by adding an extra (hidden) layer of threshold units each of which does a partial classification of the input ...

The number of hidden layers gives rise to the concept of deep learning ... In the case of supervised ANNs, researchers train the neural network by feeding in data with known values or features.

The field of AI is notoriously filled with jargon. To better understand what is going on, here is a series of explainers, which will break down some of the most common terms used in AI, and why they a ...

Studying coral reefs used to mean hours of grueling manual analysis, but artificial intelligence is changing the game. A new ...