Q2: (6 points) Assuming we aim to build a more advanced reco…

Q2: (6 points) Assuming we aim to build a more advanced recommendation system for an online bookstore using matrix factorization-based methods, similar to the one that won the Netflix prize. Suppose the global mean rating of books is 3.6 stars. Bob, a loyal customer, has rated 400 books, and his average rating is 0.3 stars higher than the global average rating. Meanwhile, Pride and Prejudice is a book in the bookstore that has 200,000 ratings, with an average rating that is 0.5 stars lower than the global average. What would be a baseline estimate of Bob’s rating for Pride and Prejudice? (2 points) Illustrate how you arrived at your answer. (2 points)

Calculate the gross autopsy rate using the information in th…

Calculate the gross autopsy rate using the information in the table below.  Express as a percent.  Round to two decimal places. Highland Hospital October-December, 20XX Discharges and deaths             Adults and children 1,070           Newborns 260 Deaths             Adults and children 31           Newborns 2 Inpatient autopsies 17 Coroner’s case (unavailable for autopsy) 3

You are measuring the relationship between two variables so…

You are measuring the relationship between two variables so you choose the CORREL function in Excel.  The correlation (r) is calculated as 0.97.  What can you conclude? Which scatter diagram would you expect to see? Scatter -0.97.png  Diagram A Scatter 0.91.png  Diagram B Scatter 0.png  Diagram C

Carlisle Community Hospital is a 324-bed hospital in Edgewat…

Carlisle Community Hospital is a 324-bed hospital in Edgewater, PA.  During 20XX,  the hospital reported 400 live births and two maternal deaths after abortions. What is the maternal mortality rate? Report the rate to the nearest tenth per 100,000.

Q4: (8 points) Designing A Machine Learning System.Given use…

Q4: (8 points) Designing A Machine Learning System.Given user features, item features, and a user-item-rating matrix, if we formulate the problem of recommending personalized items for users as a ranking task, how can we use develop a personalized Learning To Rank (LTR) model for recommendations? Please specify: how you will use the data what is your model structure what is your objective function how to use the learned ranking model to conduct personalized recommendations.