a) Select and critique an appropriate clustering algorithm for building a model using un- supervised learning. Your answer should include either a description or pseudo-code of how the algorithm works, input and output limitations, pros, cons, hyper-parameters that require optimisation and types of suitable applications. (15 Marks) b) Identify key advantages and disadvantages (in your own words) in building a recommender engine using collaborative filtering neighbourhood similarity; collaborative filtering latent factor models; content-based user profile and content-based supervised learning. (16 Marks) c) Identify an algorithm suitable for visualising high dimensional data. (4 Marks) Activate Windows Go to Settings to activate Windows.