Neural Network
A computing system inspired by biological neural networks, consisting of interconnected nodes (neurons).
In-depth explanation
Artificial neural networks process information through layers of interconnected neurons. Each connection has a weight that's adjusted during training. The input layer receives data, hidden layers process it through weighted connections and activation functions, and the output layer produces predictions. Deep neural networks have many hidden layers.
Examples
Related terms
More in Neural Networks
Neuron
A basic computational unit in a neural network that receives inputs, applies weights and activation, and produces output.
Activation Function
A mathematical function that determines the output of a neuron based on its weighted input sum.
Backpropagation
The algorithm for calculating gradients of the loss function with respect to network weights.
Epoch
One complete pass through the entire training dataset during model training.
Batch Size
The number of training examples used in one iteration of model training.
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