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IBM Watson Data Scientist v1 Sample Questions:

1. Understanding how to use libraries in Python within a deployment environment is essential for:

A) Increasing the complexity and maintenance cost of the deployed solution
B) Ensuring that all models are developed without any external libraries
C) Leveraging specific functionalities for data analysis, manipulation, and model building
D) Deploying models that are incompatible with the deployment environment

2. Selecting the right model for a data science project depends on:

A) The preference of the data scientist
B) The project's budget only
C) The size of the dataset only
D) The type of data and the problem to be solved

3. A virtual assistant has been developed and deployed based on the Watson Assistant service. The assistant will support customers by answering FAQs (Frequent Answered Questions).
Which metric is a good indicator of the performance of the virtual assistant?

A) The F1 score of predicted intents in the Analytics tab
B) The Area Under the Curve (AUC)
C) The Root Mean Squared Error (RMSE) of words
D) Measure escalated calls using A/B testing

4. When selecting a small number of algorithms based on model requirements, what factor should you primarily consider?

A) Compatibility of the algorithm with the data characteristics and the predictive task.
B) The algorithm that requires the least amount of data preprocessing.
C) Choosing algorithms that are only based on supervised learning.
D) The popularity of the algorithm in recent academic papers.

5. Which of the following is true about the AUC measure in the context of classification models?

A) It measures the model's accuracy using a single threshold.
B) It represents the degree of separability between classes.
C) It indicates the number of false positives.
D) It is less useful when the classes are highly imbalanced.

Solutions: