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A data scientist is exploring transaction data from a chain of stores with several locations. The data includes store number, date of sale, and purchase amount.
If the data scientist wants to compare total monthly sales between stores, which two options would be good ways to aggregate the data? (Choose two.)
What is a class of machine learning problems where the algorithm builds a mathematical model from a set of data that contains both the inputs and the desired outputs?
What are two hyperparameters used when building a k-means model? (Choose two.)
In a hyperparameter search, whether a single model is trained or a lot of models are trained in parallel is largely determined by?
What is a class of machine learning problems where the algorithm is given feedback in the form of positive or negative reward in a dynamic environment?
