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The human brain is made up of approximately 86 billion biological neurons connected by synapses. When we learn something new, the connections between these neurons strengthen or weaken.
Artificial Neural Networks (ANNs) are mathematical models loosely inspired by this biological process. Instead of biological cells, we use nodes (artificial neurons) and weights (synaptic connections).
To understand a massive Deep Learning network, we must first understand its smallest individual component: The Perceptron.
