Free CompTIA DataX Certification Exam DY0-001 Exam Practice Test

The most likely concern with a one-feature, machine-learning model is high error due to:

• bias
• dimensionality.
• variance.
• probability.

A data scientist is building a forecasting model for the price of copper. The only input in this model is the daily price of copper for the last ten years. Which of the following forecasting techniques is the most appropriate for the data scientist to use?

• Autoregressive
• Moving average
• Dynamic time warping
• Relative strength

Which of the following environmental changes is most likely to resolve a memory constraint error when running a complex model using distributed computing?

• Converting an on-premises deployment to a containerized deployment
• Migrating to a cloud deployment
• Moving model processing to an edge deployment
• Adding nodes to a cluster deployment

A data analyst is examining the correlation matrix of a new data set to identify issues that could adversely impact model performance. Which of the following is the analyst most likely checking for?

• Undersampling
• Multicollinearity
• Oversampling
• Overfitting

In a modeling project, people evaluate phrases and provide reactions as the target variable for the model. Which of the following best describes what this model is doing?

• Sentiment analysis
• Named-entity recognition
• TF-IDF vectorization
• Part-of-speech tagging

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?

• The model should be deployed because it has a lower RMSE.
• The model's adjusted R2 is exceptionally strong for such a complex relationship.
• The model fails to improve meaningfully on the benchmark model.
• The model's adjusted R2 is too low for the real estate industry.

Under perfect conditions, E. coli bacteria would cover the entire earth in a matter of days. Which of the following types of models is the best for explaining this type of growth?

• Linear
• Logarithmic
• Polynomial
• Exponential

A data scientist is preparing to brief a non-technical audience that is focused on analysis and results. During the modeling process, the data scientist produced the following artifacts:Charts and dashboardsModel performance statistics (accuracy, precision, recall, F1 score, etc.)Mathematical descriptions of clustering algorithms included in the selected modelModel selection, justification, and purposeCode documentationData dictionaryWhich of the following artifacts should the data scientist include in the briefing? (Choose two.)

• Final charts and dashboards
• Model selection, justification, and purpose
• Code documentation
• Mathematical descriptions of clustering algorithms included in the selected model
• Model performance statistics (accuracy, precision, recall, F1_ score, etc.)
• Data dictionary

Which of the following JOINS would generate the largest amount of data?

• RIGHT JOIN
• LEFT JOIN
• CROSS JOIN
• INNER JOIN

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

• |e|
• e
• e2