Free DY0-001 Exam Dumps Preview

A data scientist built several models that perform about the same but vary in the number of features.

Which of the following models should the data scientist recommend for production according to Occam's razor?

A data scientist needs to:

Build a predictive model that gives the likelihood that a car will get a flat tire.

Provide a data set of cars that had flat tires and cars that did not.

All the cars in the data set had sensors taking weekly measurements of tire pressure similar to the sensors that will be installed in the cars consumers drive.

Which of the following is the most immediate data concern?

Which of the following techniques enables automation and iteration of code releases?

A data scientist is clustering a data set but does not want to specify the number of clusters present.

Which of the following algorithms should the data scientist use?

A data scientist trained a model for departments to share. The departments must access the model using HTTP requests.

Which of the following approaches is appropriate?

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 computer vision model is trained to identify cats on a training set that is composed of both cat and dog images. The model predicts a picture of a cat is a dog.

Which of the following describes this error?

Which of the following best describes the minimization of the residual term in a ridge linear regression?

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 R?of 0.75. 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 explains back propagation?

A statistician notices gaps in data associated with age-related illnesses and wants to further aggregate these observations.

Which of the following is the best technique to achieve this goal?

A data scientist is analyzing a data set with categorical features and would like to make those features more useful when building a model.

Which of the following data transformation techniques should the data scientist use? (Choose two.)

The following graphic shows the results of an unsupervised, machine-learning clustering model:

k is the number of clusters, and n is the processing time required to run the model.

Which of the following is the best value of k to optimize both accuracy and processing requirements?