?What is the purpose of an activation function in a neural network

Activation functions introduce non-linearity to the neural network, enabling it to learn complex patterns and relationships in the data. They determine whether a neuron should be activated or not based on the weighted sum of inputs. Popular activation functions include sigmoid, tanh, ReLU, and softmax.

?What role does backpropagation play in training neural networks

Backpropagation is a key algorithm for training neural networks. It works by adjusting the weights of the connections between neurons based on the difference between the predicted output and the actual output. By iteratively propagating this error backward through the network and updating the weights accordingly, backpropagation enables the neural network to learn and improve its performance over time.

Neural network fundamentals and deep learning

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