What role does the learning rate play in the Steepest Descent method? a. It represents the error function b. It determines the size of the incremental steps in updating parameters c. It is the output of the input layer d. It represents the difference between true output and observed output

How are gradient descent and learning rate used in logistic regression? 1 pointGradient descent takes increasingly bigger steps towards the minimum with each iteration.Gradient descent will minimize learning rate to minimize the cost in fewer iterations.Gradient descent specifies the steps to take in the current slope direction, learning rate is the step length.We want to minimize the cost by maximizing the learning rate value.

What is the learning rate in backpropagation?Select one:a.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 hyperparameter that determines the size of the weight and bias updates

Which of the following statements about Gradient Descent are true? (Select all that apply)Group of answer choicesLearning rate is a crucial hyperparameter in its performance.It requires calculation of gradients for the entire dataset.It can be very slow when the dataset is very large.It is guaranteed to find the global minimum for non-convex functions.

What is the purpose of the learning rate in neural network optimization?Review LaterTo control the number of epochsTo determine the batch sizeTo adjust the step size during weight updatesTo set the initial weights

In gradient descent algo, small learning rate _____.1 pointovershoot, become stable and divergeovershoot, become unstable and divergeovershoot, become stable and convergeNone of the above