In other words, it can determine which variables affect your model's output and which do not. The backpropagation algorithms calculate the gradient of a loss function. You can guide neural networks using backpropagation and gradient descent algorithms. Next, it passes through the third layer until it reaches the final output. The next layer modifies the data in a particular way. The first layer receives input and then passes it to the next layer. Neural network algorithms consist of connected nodes in layers.
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