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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. 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

2. What is a critical consideration when selecting the right model class for a given problem?

A) The availability of high-performance computing resources.
B) The model's ability to produce results quickly, regardless of accuracy.
C) The theoretical complexity of the model, with more complex models always being preferred.
D) The nature of the problem (e.g., classification, regression) and the characteristics of the data.

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

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

4. Which two graph types are used in EDA to show the relationship between two or more quantitative variables?

A) Box plot
B) Scatter plot
C) Stem-and-leaf plot
D) Histogram
E) Heat map

5. What does the term "complexity" in model comparison refer to?

A) The aesthetic appeal of the model's graphical representations
B) The size of the dataset the model can handle
C) The amount of computational resources required for training and inference
D) The number of hyperparameters that need to be tuned

Solutions: