C1000-177 시험 - IBM실제시험문제와 답 - 61문항

Question No : 1

What considerations should be made when evaluating the ethical implications of a business problem? (Choose Three)

A.Potential for AI to replace human jobs
B.Environmental impact of AI solutions
C.Impact on company profit margins
D.Consequences for user privacy and autonomy
E.Speed of implementation

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Question No : 2

Why is logistic regression considered a linear classifier?

A.Because it is only capable of linear regression tasks
B.Because it uses a linear decision boundary to separate classes
C.Because it applies a nonlinear transformation to the input features
D.Because it computes the decision boundary using a non-linear optimization

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Question No : 3

Which practice is least effective in configuring environments for training machine learning models?

A.Using virtual environments to manage dependencies
B.Using the latest but unstable software versions
C.Regularly updating libraries to their stable versions
D.Allocating resources based on model requirements

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Question No : 4

What are two reasons a data point would be treated as an outlier?

A.If the value is greater than mean
B.If the value is greater than median
C.If the value is greater than standard deviation
D.If the value is below the upper end of the bottom quartile by more then 1.5 times the interquartile range
E.If the value is above the lower end of the top quartile by more then 1.5 times the interquartile range

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Question No : 5

For implementing dimensional reduction, which method would be most effective when dealing with highly nonlinear data?

A.Linear Discriminant Analysis (LDA)
B.PCA
C.t-Distributed Stochastic Neighbor Embedding (t-SNE)
D.Factor Analysis

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Question No : 6

How does feature scaling benefit the process of exploratory data analysis?

A.It changes the underlying data distribution
B.It makes different variables comparable
C.It simplifies the database management system
D.It eliminates the need for data cleaning

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Question No : 7

Which feature engineering technique can be used to simplify models and improve interpretability?

A.One-hot encoding categorical variables
B.Normalizing continuous variables
C.Removing correlated features
D.Increasing the number of features

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Question No : 8

When monitoring models in production, what aspect is crucial for maintaining long-term reliability?

A.Regularly updating the user interface
B.Ensuring the model is scalable to handle increased loads
C.Reducing the number of inputs to the model
D.Focusing solely on increasing model speed

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Question No : 9

In assessing progress on the AI Ladder, which aspects should be considered? (Choose Two)

A.The quality and accessibility of data
B.The color palette of the user interface
C.Integration capabilities with existing systems
D.Branding and marketing strategies

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Question No : 10

How does IBM Garage Methodology suggest measuring success for an MVP?

A.By the number of features implemented
B.Through stakeholder satisfaction and feedback
C.By comparing the MVP to competitor products
D.Solely by financial metrics achieved

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Question No : 11

What is the first step in aligning on user intents for an AI solution?

A.Prototyping the solution
B.Identifying key stakeholders
C.Conducting a market analysis
D.Documenting technical requirements

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Question No : 12

What is the primary use of the WHERE clause in an SQL query?

A.To specify which columns to retrieve
B.To limit the data that fits certain conditions
C.To identify the tables involved in the query
D.To denote the end of the SQL query

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Question No : 13

How do you assess the feasibility of an AI solution?

A.By evaluating the available technology and resources
B.By creating detailed financial models only
C.By ensuring the project is the top priority of the organization
D.By hiring external consultants to validate the solution

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Question No : 14

Which of the following are considered direct effects of an AI solution? (Choose Two)

A.Enhancements in process efficiency for which the AI was designed
B.Increased job satisfaction among employees not using the AI directly
C.Reduction in operational costs due to automation
D.New market opportunities stemming from the innovation

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Question No : 15

In the context of classification, what does the term 'overfitting' refer to?

A.The model performs equally well on the training and test datasets
B.The model performs poorly on both training and test datasets
C.The model performs too well on the training dataset but poorly on unseen data
D.The model requires too much time to train due to large dataset

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IBM C1000-177 시험