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1. Refer to the exhibit below:

Based on the output from the Data Exploration node shown in the exhibit, which variable has the most thin tails (most platykurtic distribution)?

2. Given the following properties for a neural network model, which statement is true regrading hidden units in the model? The following SAS program is submitted:

3. Which of the following is an example of a NoSQL database that is commonly used to store unstructured data?

4. What is the primary goal of A/B testing in the context of model deployment?

5. What does the term "bias" in machine learning refer to?

6. What is the significance of the "bias-variance trade-off" in machine learning?

7. What is the purpose of cross-validation in model building and evaluation?

8. What is the purpose of a "canary release" in the context of model deployment?

9. When deploying a machine learning model, what is "model drift"?

10. Which algorithm is commonly used for decision-making tasks in classification models?

11. What is the primary purpose of model documentation in the model deployment phase?

12. Which of the following best describes unstructured data?

13. What is the main advantage of using a RESTful API (Representational State Transfer) as a data source?

14. Which statements are true for the F1 score?

(Choose 2.)

15. Which type of model is commonly used for anomaly detection in datasets?

16. What does API stand for in the context of data sources?

17. Which data source allows for real-time data streaming and processing?

18. What is the main advantage of ensemble methods in model building?

19. Which machine learning technique is typically used for building a model to predict a numeric target variable?

20. Refer to the treemap shown in the exhibit below:

Which statement is true about the tree map for a decision tree with a binary target?

21. What is the primary purpose of model assessment in the context of data science and machine learning?

22. What is the main advantage of ensemble learning methods, such as Random Forest, in a machine learning pipeline?

23. When deploying a machine learning model, what is meant by "model latency"?

24. What is the purpose of an ROC curve (Receiver Operating Characteristic) in model assessment?

25. Which data source typically provides access to real-time financial market data?

26. In model assessment, what does "cross-validation" aim to address?

27. Which metric is commonly used to evaluate the performance of a regression model?

28. What is "model reevaluation" in the model deployment phase?

29. What is overfitting in machine learning, and how can it be addressed in a pipeline?

30. What is a data lake?