Answer the following questions with respect to Machine Learning algorithms. a) Describe two real-life Machine Learning applications in which classification might be useful. Describe the response, as well as the predictors. Is the goal of each application inference or prediction? Explain your answer. b) There are many different clustering algorithms in the field of data science. One common approach is to divide the data points in a way that each data point falls into a group that is similar to other data points in the same group based on a predefined similarity or distance metric in the feature space. Clustering is commonly used for determining customer segments in marketing data. Being able to determine different segments of customers helps marketing teams approach these customer segments in unique ways. (Think of features like gender, location, age, education, income bracket, and so on.) Is clustering a Supervised Learning problem or an Unsupervised Learning problem? Explain why? [5]