See the following image for logreg.py:

3. Gradient Descent: Logistic Regressiorn SENG 474; CSC578D: 15 points) For this question, we will implement logistic regression, and test it using the breast cancer dataset and the code skeleton in logreg.py. For this question, you only need to implement batch gradient descent. This time, plot the log likelihood function for each iteration: Test it with a few different learning rates. Eg. K is happening. [15 pts] 0.001, 0.01, 0.1. Explain what 3. Gradient Descent: Logistic Regressiorn SENG 474; CSC578D: 15 points) For this question, we will implement logistic regression, and test it using the breast cancer dataset and the code skeleton in logreg.py. For this question, you only need to implement batch gradient descent. This time, plot the log likelihood function for each iteration: Test it with a few different learning rates. Eg. K is happening. [15 pts] 0.001, 0.01, 0.1. Explain what