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New C1000-154 Dumps Questions - Original C1000-154 Questions

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IBM Watson Data Scientist v1 Sample Questions (Q40-Q45):

NEW QUESTION # 40
The first step in performing exploratory data analysis (EDA) typically involves:

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

Answer: B

NEW QUESTION # 41
A model's performance is not solely dependent on its accuracy but also on:

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

Answer: D

NEW QUESTION # 42
In IBM Garage Methodology, the 'Minimum Viable Product' (MVP) concept is crucial for:

A. Testing hypotheses with the smallest investment of time and resources
B. Waiting for all possible features to be developed before release
C. Extending the timeline of the project indefinitely
D. Maximizing the budget before the product launch

Answer: A

NEW QUESTION # 43
Assessing the feasibility of a solution(s) often requires evaluating:

A. The color scheme of the user interface
B. Technical feasibility, cost, and time constraints
C. Market competition only
D. Preferred communication channels of the project manager

Answer: B

NEW QUESTION # 44
Key metrics for a solution should be defined based on:

A. The personal preferences of the project stakeholders
B. The most recent technological trends
C. The number of available data scientists
D. The specific objectives and desired outcomes of the project

Answer: D

NEW QUESTION # 45
......

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