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 main goal of the backpropagation algorithm?Select one:a.To minimize the error between the predicted output and the actual outputb.To maximize the accuracy of the modelc.To minimize the accuracy of the modeld.To maximize the error between the predicted output and the actual output

What is the gradient descent in the backpropagation algorithm?Question 6Answera.The process of minimizing the error between the predicted output and the actual outputb.The process of adjusting the weights and biases in the forward directionc.The process of adjusting the weights and biases in the backward directiond.The process of maximizing the error between the predicted output and the actual output

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 primary purpose of the backpropagation algorithm in training a neural network?ATo compute the output of the networkBTo initialize the weights of the networkCTo update the weights of the network by minimizing the loss functionDTo determine the optimal network architecture

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