An Artificial Neural Network (ANN) is a computational model inspired by the way the human brain works. In our brain, billions of neurons are connected and transmit signals to process information. Similarly, an ANN is made up of interconnected nodes (called artificial neurons) that can receive input, process it, and pass it forward to the next layer.Neural networks form the core of Machine Learning (ML) and Deep Learning (DL), enabling computers to learn patterns, recognize data, and make decisions just like humans.Forward Propagation → Data flows from input to output through hidden layers.Loss Calculation → The difference (error) between predicted output and actual output is calculated.Backpropagation → The network adjusts its weights and biases to reduce the error.Training Loop → Steps are repeated thousands (or millions) of times until the network learns accurately.
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