Question $9$

Training a perceptron model by gradient descent

vs$.$ that of a logistic regression model

is easier due to sigmoid activation function with positive derivative

is harder due to step activation function in the perceptron model

none of them can be trained $($optimized$)$

Is the same as their decision boundaries are similar