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IBM Watson Data Scientist v1 Sample Questions:

1. How do you determine which tool to use based on algorithm requirements and expertise?

A) Choose the newest tools on the market for the most up-to-date features.
B) Always use the most complex tool to ensure the model's accuracy.
C) Select tools that the team is already familiar with, even if they are not the best fit for the algorithm.
D) Consider the tool's compatibility with the algorithm requirements and the team's expertise.

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

3. In the context of avoiding underfitting and overfitting, what role does splitting the data into training, testing, and validation sets play?

A) It allows for the model to be validated and tested on different subsets of data to check its generalization ability
B) It ensures that the model is trained on the maximum amount of data possible
C) It increases the computational complexity without improving model performance
D) It guarantees that the model will perform with 100% accuracy on unseen data

4. In Cognos Analytics, which two features distinguish stories from dashboards?

A) Stories provide a narrative over time.
B) Stories automatically load different filters for different users.
C) Stories convey a conclusion.
D) Stories can be embedded in websites or documents.
E) Stories are text-based and do not contain visualizations.

5. What is a key disadvantage of using Grid Search for hyperparameter tuning?

A) It is too quick and may miss out on evaluating some hyperparameters
B) It is unable to handle discrete parameters
C) It can be computationally expensive and time-consuming due to its exhaustive nature
D) It requires no prior knowledge of the hyperparameters

Solutions: