As mentioned above “backpropagation” is an algorithm which uses supervised learning methods to compute the gradient descent (delta rule) with respect to weights. as per wiki – “backpropagation is a method used in artificial neural networks to calculate a gradient that is needed in the calculation of the weights to be used in the network. Python program for backpropagation. a neural network is a network structure, by the presence of computing units (neurons) the neural network has gained the ability to compute the function. the neurons are connected with the help of edges, and it is said to have an assigned activation function and also contains the adjustable parameters.
By v sharma. backpropagation algorithm – an important mathematical tool for making better and higher accuracy predictions in machine learning. this algorithm uses supervised learning methods for training artificial neural networks. backpropagation, short for “backward propagation of errors,” is a fundamental algorithm in training neural. In the context of learning, backpropagation is commonly used by the gradient descent optimization algorithm to adjust the weight of neurons by calculating the gradient of the loss function. The basic process of deep learning is to perform operations defined by a network with learned weights. for example, the famous convolutional neural network (cnn) is just multiplying, adding, etc., pixel intensity values with such rules designed by the network. then, if we want to classify whether the picture is a dog or a cat, we should somehow. Backpropagation algorithm – an important mathematical tool for making better and higher accuracy predictions in machine learning. this algorithm uses supervised learning methods for training.
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