Question $4(2$ points$)$ Use Python to compute the cosine similarity between users. Hint: see below how to calculate the similarity for missing data. Question $5(2$ points$)$ Based on the cosine similarities of the nearest students to E$.$N$.,$ which course should be recommended to E$.$N$.?$ Question $6(2$ points$)$ With large datasets, it is computationally difficult to compute user$-$based recommendations in real time, and an item$-$based approach is used instead. Returning to the rating data $($not the binary matrix$),$ let$$s now take that approach. $(1$ point$)$ If the goal is still to find a recommendation for E$.$N$.,$ for which course pairs is it possible and useful to calculate correlations? $(1$ point$)$ Just looking at the data, and without yet calculating course pair correlations, which course would you recommend to E$.$N$.,$ relying on item$-$based filtering? Calculate two course pair correlations involving your guess and report the results