Prerequisites In this assignment you will implement the Naive Bayes Classifier. Before starting this assignment, make sure you understand the concepts discussed in the videos in Week 2 about Naive Bayes. You can also find it useful to read Chapter 1 of the textbook. Also, make sure that you are familiar with the numpy.ndarray class of python's numpy library and that you are able to answer the following questions: Let's assume a is a numpy array. What is an array's shape (e.g., what is the meaning of a.shape)? What is numpy's reshaping operation? How much computational over-head would it induce? What is numpy's transpose operation, and how it is different from reshaping? Does it cause computation overhead? What is the meaning of the commands a.reshape(-1, 1) and a.reshape(-1)? Would happens to the variable a after we call b = a.reshape(-1)? Does any of the attributes of a change? How do assignments in python and numpy work in general? Does the b=a statement use copying by value? Or is it copying by reference? Would the answer to the previous question change depending on whether a is a numpy array or a scalar value? You can answer all of these questions