A data scientist is building a model to predict customer credit scores based on information collected from reporting agencies. The model needs to automatically adjust its parameters to adapt to recent changes in the information collected. Which of the following is the best model to use?
A data scientist is creating a responsive model that will update a product's daily pricing based on the previous day's sales volume. Which of the following resource constraints is the data scientist's greatest concern?
A data scientist wants to predict a person's travel destination. The options are:Branson, Missouri, United StatesMount Kilimanjaro, Tanzania -Disneyland Paris, Paris, France -Sydney Opera House, Sydney, AustraliaWhich of the following models would best fit this use case?
A data scientist is working with a data set that has ten predictors and wants to use only the predictors that most influence the results. Which of the following models would be the best for the data scientist to use?
A data scientist uses a large data set to build multiple linear regression models to predict the likely market value of a real estate property. The selected new model has an RMSE of 995 on the holdout set and an adjusted R2 of .75. The benchmark model has an RMSE of 1,000 on the holdout set. Which of the following is the best business statement regarding the new model?
Which of the following layer sets includes the minimum three layers required to constitute an artificial neural network?
