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IBM Watson Data Scientist v1 Sample Questions:

1. 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 popularity of the algorithm in recent academic papers.
C) Choosing algorithms that are only based on supervised learning.
D) The algorithm that requires the least amount of data preprocessing.

2. 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) Deploying models that are incompatible with the deployment environment
C) Leveraging specific functionalities for data analysis, manipulation, and model building
D) Ensuring that all models are developed without any external libraries

3. Which statement describes bagging?

A) Building models with artificial neural networks based on the sharedweight architecture of the convolution kernels or filters.
B) Building models in parallel and aggregating their predictions to select the final prediction.
C) Building models sequentially and evaluating the success of earlier models. It combines a set of weak learners into a strong learner.
D) Building models and using their output as features into a final model.

4. When determining upskill requirements for a team working on a solution, it is important to consider:

A) The geographical location of the team members
B) The budget allocation for the project
C) The preferred programming languages of the team
D) The existing skill level of the team and the skills required for the project

5. The ROC curve is a graphical representation that shows the performance of a classification model at all classification thresholds.
What does ROC stand for?

A) Random Output Curve
B) Recall Operation Curve
C) Regression Operation Characteristic
D) Receiver Operating Characteristic

Solutions: