In the context of ML, Artificial Neural Networks are computing systems that “learn” to perform tasks by considering examples, generally without being programmed with a specific task. The network is based on a collection of connected nodes called “neurons”. Each connection can transmit a signal (value) from one neuron to another. A neuron that receives a signal, process it and then signal additional neurons connected to it.