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What is the gradient descent in the backpropagation algorithm?Question 11Answera.The process of adjusting the weights and biases in the backward directionb.The process of minimizing the error between the predicted output and the actual outputc.The process of adjusting the weights and biases in the forward directiond.The process of maximizing the error between the predicted output and the actual output

Question

What is the gradient descent in the backpropagation algorithm?Question 11Answera.The process of adjusting the weights and biases in the backward directionb.The process of minimizing the error between the predicted output and the actual outputc.The process of adjusting the weights and biases in the forward directiond.The process of maximizing the error between the predicted output and the actual output

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Solution

The gradient descent in the backpropagation algorithm refers to the process of minimizing the error between the predicted output and the actual output by adjusting the weights and biases in the backward direction. So, the correct answer is a combination of options a and b.

Similar Questions

What is the bias update rule in the backpropagation algorithm?Question 18Answera.The mathematical formula that is used to update the biases based on the gradient descentb.The process of adjusting the weights and biases in the forward directionc.The process of minimizing the error between the predicted output and the actual outputd.The process of adjusting the weights and biases in the backward direction

What is the backward pass in the backpropagation algorithm?Question 20Answera.The process of adjusting the weights and biases in the forward directionb.The process of calculating the error between the predicted output and the actual outputc.The process of adjusting the weights and biases in the backward directiond.The process of predicting the output of the neural network based on the input data

What is the learning rate in backpropagation?Question 1Answera.The process of minimizing the error between the predicted output and the actual outputb.The process of adjusting the weights and biases in the backward directionc.The hyperparameter that determines the size of the weight and bias updatesd.The process of adjusting the weights and biases in the forward direction

What is the goal of the backpropagation algorithm in each iteration?Question 4Answera.To minimize the error between the predicted output and the actual outputb.To maximize the error between the predicted output and the actual output in each iterationc.To maximize the error between the predicted output and the actual outputd.To minimize the error between the predicted output and the actual output in each iteration

What is the error function in the backpropagation algorithm?Question 5Answera.The function that adjusts the weights and biases in the forward passb.The function that calculates the error between the predicted output and the actual outputc.The function that determines the activation function of the neural networkd.The function that adjusts the weights and biases in the backward pass

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