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backpropagation

 

Definitions from the Web

Backpropagation

Definition

Backpropagation is a commonly used algorithm in the field of artificial intelligence and machine learning. It is primarily utilized to train artificial neural networks.

Senses and Usages

Sense 1 - Artificial Neural Networks

In the context of artificial neural networks, backpropagation is a supervised learning algorithm used for training multi-layer perceptrons. It involves propagating errors backward from the output layer to the input layer, adjusting the weights and biases of each neuron to minimize the overall error.

Sample Sentence 1: Backpropagation is an efficient method for training neural networks due to its ability to adjust weights based on error feedback.

Sample Sentence 2: The network achieved remarkable accuracy after several iterations of backpropagation.

Sense 2 - Mathematics

In mathematics, backpropagation is often studied as a method to calculate the gradient of a function with respect to its inputs. It is widely used in optimization algorithms such as gradient descent.

Sample Sentence 1: Backpropagation simplifies the computation of gradients, enabling efficient optimization of complex functions.

Sample Sentence 2: The algorithm employs backpropagation to update the parameters of the objective function.

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