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The term "greedy algorithms" refers to machine-learning algorithms that:
A data scientist is deploying a model that needs to be accessed by multiple departments with minimal development effort by the departments. Which of the following APIs would be best for the data scientist to use?
Which of the following compute delivery models allows packaging of only critical dependencies while developing a reusable asset?
A data analyst is analyzing data and would like to build conceptual associations. Which of the following is the best way to accomplish this task?
Which of the following belong in a presentation to the senior management team and/or C-suite executives? (Choose two.)
During EDA, a data scientist wants to look for patterns, such as linearity, in the data. Which of the following plots should the data scientist use?
Which of the following distribution methods or models can most effectively represent the actual arrival times of a bus that runs on an hourly schedule?
A data scientist has constructed a model that meets the minimum performance requirements specified in the proposal for a prediction project. The data scientist thinks the model's accuracy should be improved, but the proposed deadline is approaching. Which of the following actions should the data scientist take first?
Which of the following best describes the minimization of the residual term in a ridge linear regression?
A data scientist is performing a linear regression and wants to construct a model that explains the most variation in the data. Which of the following should the data scientist maximize when evaluating the regression performance metrics?
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 needs to analyze a company's chemical businesses and is using the master database of the conglomerate company. Nothing in the data differentiates the data observations for the different businesses. Which of the following is the most efficient way to identify the chemical businesses' observations?
Which of the following distance metrics for KNN is best described as a straight line?
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?
An analyst wants to show how the component pieces of a company's business units contribute to the company's overall revenue. Which of the following should the analyst use to best demonstrate this breakdown?
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Log In / Sign UpWhich of the following issues should a data scientist be most concerned about when generating a synthetic data set?
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?
