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.

Q6: (4 points)What is the strategy of AdaBoosting for reweighing the training data points?

Q4: (3 points) Answer True or False only: In DQN, the Q value function is instantiated by a neural network.

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)

Which of the following is considered a regulated waste under the Bloodborne Pathogens Standard?

Which hazard class is used for substances causing skin corrosion?

Formaldehyde exposure symptoms include:

Employers must provide bloodborne pathogen training to employees at what frequency?

How many sections must be included in a compliant SDS?

The best example of a work practice control is: