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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

Question 1

In classification models, which of the following metrics is NOT directly derived from the confusion matrix?

A. Recall
B. Precision
C. Mean Absolute Error (MAE)
D. F1-score

Question 2

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

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

Question 3

How does the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology begin its process model?

A. Evaluation
B. Model Building
C. Data Preparation
D. Business Understanding

Question 4

When managing data with Cloud Pak for Data Services, what is a common task?

A. Ignoring data security and compliance requirements
B. Reading data from and writing data to Watson Studio
C. Avoiding the automation of data processing tasks
D. Using the same data management approach for all types of data, regardless of size or format

Question 5

When would you use AutoAI to select algorithms for your model?

A. Only when working with small datasets due to processing limitations.
B. When you want to automatically explore multiple algorithms and hyperparameters to find the best model.
C. When the model requirements are extremely specific and no standard algorithm fits.
D. When you have a deep understanding of all available algorithms and want to manually tune hyperparameters.

Solutions: