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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. A model's performance is not solely dependent on its accuracy but also on:

A) Metrics like precision, recall, and F1 score
B) The color of the visualization charts
C) The choice of programming language
D) The number of features selected

2. Why is it important to create data splits that are reproducible?

A) To allow for larger test sets for more comprehensive testing
B) To ensure that each model run can be exactly replicated for verification and comparison
C) To use more data for testing than for training
D) To guarantee that the model will perform with 100% accuracy on unseen data

3. When using pandas in a Jupyter notebook for exploratory data analysis, what is a common practice?

A) Utilizing pandas to clean and transform data
B) Only analyzing datasets with less than 100 rows
C) Avoiding the use of visualizations to understand data
D) Ignoring missing values in the dataset

4. In defining a business problem, what is essential to align with the stakeholders?

A) Business objectives
B) Technical requirements
C) Data sources
D) Project milestones

5. Which hyperparameter is NOT commonly adjusted in a deep learning model?

A) Activation function
B) Number of layers
C) The color of the model's output
D) Learning rate

Solutions: