C1000-154 by IBM Actual Free Exam Q&As

Question 1

Choosing the best model often involves trade-offs.
Which scenario represents such a trade-off?

A. Preferring a model with higher accuracy over one that is slightly less accurate but much more interpretable B. Opting for the most complex model to ensure ease of use C. Choosing the model with the largest number of features, regardless of performance D. Selecting a model based solely on its execution speed, without regard to accuracy

Discussion 0

Correct Answer: A Vote an answer

Question 2

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

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

Discussion 0

Correct Answer: A Vote an answer

Question 3

Which of the following best describes when to use deep learning over traditional machine learning algorithms?

A. When working with high-dimensional data, such as images or natural language, where feature extraction is complex. B. When computational resources are limited and model interpretability is not a concern. C. For simple tasks that require straightforward predictive modeling. D. When the dataset is small and easily interpretable.

Discussion 0

Correct Answer: A Vote an answer

Question 4

The first step in performing exploratory data analysis (EDA) typically involves:

A. Determining the hypothesis for the analysis B. Choosing a color palette for data visualization C. Connecting to as many data sources as possible D. Selecting a random sample of data to analyze

Discussion 0

Correct Answer: A Vote an answer

Question 5

When helping businesses articulate and define problems, what is an essential first step?

A. Identifying potential data sources B. Selecting the analytical techniques C. Establishing a clear problem statement D. Defining key performance indicators (KPIs)

Discussion 0

Correct Answer: C Vote an answer

Question 6

Profiling and visualizing data using Watson tools primarily helps in:

A. Increasing the quantity of data for analysis B. Creating aesthetically pleasing presentations without regard to data relevance C. Identifying patterns, outliers, and insights in the data D. Simplifying the data collection process without analyzing quality

Discussion 0

Correct Answer: C Vote an answer

Question 7

In the context of deployment environments, understanding resources is crucial.
What does this typically involve?

A. Focusing exclusively on the cost of storage B. Determining the computational power and memory requirements for the deployed solution C. Choosing the most aesthetically pleasing user interface D. Selecting the programming language with the least number of keywords

Discussion 0

Correct Answer: B Vote an answer

Question 8

What is the primary purpose of hyperparameter tuning in machine learning models?

A. To ensure the model uses all available computational resources B. To reduce the training time of the model to an absolute minimum C. To increase the number of features in the dataset automatically D. To adjust the model's complexity to improve its performance on unseen data

Discussion 0

Correct Answer: D Vote an answer

Question 9

Which metric would be most appropriate for evaluating a model in a highly imbalanced classification problem?

A. Recall B. Accuracy C. Precision D. F1-score

Discussion 0

Correct Answer: D Vote an answer

IBM Watson Data Scientist v1 - C1000-154 Exam Practice Test