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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. When deploying models in Watson Machine Learning, what is essential for ensuring the models perform as expected in production?

A) Using the highest number of resources for every model
B) Limiting access to the model to a few select users
C) Deployment without any security measures
D) Continuous monitoring and evaluation of model performance

2. In the case of imbalanced data, what technique is recommended to ensure that the train and test sets have similar distributions of the target variable?

A) Splitting based on the order of data collection
B) Stratified split
C) Random split without considering the target variable
D) Using only the majority class for splitting

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

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

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

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

5. To add data assets from the catalog to a project in Cloud Pak for Data, which step is essential?

A) Browsing data assets based solely on their names
B) Maximizing the volume of data regardless of relevance
C) Selecting random data sets for variety
D) Assessing the compatibility of data formats

Solutions: