How to implement a logistic regression classifier using gradient ascent in the simple case where there is only one feature variable x1:

Normalize the feature variable x1 (Can Provide details on it).

• Calculate the value of the objective function l(β0,β1).

• Choose a value of the learning rate η (Can we try different values?).

• Initialize the parameter value and calculate the gradient ∇l(β0,β1).

• Update the parameter value.

• Check whether gradient ascent has converged.

(Here, We can rather look at the convergence of the values of l(β0,β1) than the convergence of the parameters themselves.)

• Complete the implementation of gradient ascent.