Convolution, Cnn, Machinelearningalgorithms, Deep Learning, Relu.
Optimization: During training, the network learns to adjust the weights and biases using backpropagation and optimization algorithms (e.g., gradient descent). The loss function measures the difference between the predicted output and the true target, and the network aims to minimize this loss.