Neural Network

In more detail

Neural networks process information through layers of interconnected artificial neurons. Each neuron receives inputs, applies a weight and bias, and passes through an activation function to produce output. The network learns by adjusting these weights and biases through backpropagation during training. Neural networks are fundamental to deep learning.

Examples

• Feedforward networks
• Convolutional neural networks for image processing
• Recurrent neural networks for sequences
• Transformer models for language

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