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NEW QUESTION # 21
A retail company has a large dataset of customer purchases but no predefined labels. The AI system groups customers into segments based on similar buying behavior. This is an example of ______.
Answer: C
Explanation:
Unsupervised learning is the correct answer because the dataset does not contain predefined labels or known target outcomes. The AI system is identifying natural patterns in the data and grouping customers with similar purchasing behavior. This type of task is commonly called clustering, which is one of the most common applications of unsupervised learning. Supervised learning is incorrect because there are no labeled examples telling the model which customer belongs to which segment. Reinforcement learning is incorrect because the system is not learning through rewards or penalties. Transfer learning involves reusing knowledge from one trained model for another related task, which is not described here. Semi-supervised learning would involve both labeled and unlabeled data, but this scenario only mentions unlabeled data. Therefore, the correct answer is B. unsupervised learning .
NEW QUESTION # 22
Unsupervised learning is a type of machine learning where the algorithm learns from a ______.
Answer: C
Explanation:
The correct answer is B. Unlabeled dataset . Unsupervised learning is a machine learning approach where the algorithm works with data that does not contain predefined labels, target outputs, or correct answers. Instead of being told what each data point represents, the model analyzes the structure of the data and identifies hidden patterns, groupings, similarities, or relationships on its own.
This type of learning is commonly used for clustering, association rule mining, anomaly detection, dimensionality reduction, and customer segmentation. For example, an unsupervised learning model may group customers based on buying behavior without being given category labels in advance.
A labeled dataset is used in supervised learning, where the model learns from input-output pairs. An
"explained dataset" is not a standard machine learning category. Since unsupervised learning specifically depends on unlabeled data, the correct answer is B. Unlabeled dataset .
NEW QUESTION # 23
Supervised learning is a type of machine learning where the algorithm learns from a ______.
Answer: B
Explanation:
The correct answer is A. labeled dataset . Supervised learning is a machine learning method in which an algorithm is trained using data that already contains the correct output labels or target values. Each training example includes input features and a known answer, allowing the model to learn the relationship between the inputs and the expected output. Once trained, the model can use that learned relationship to classify or predict outcomes for new data.
An unlabeled dataset is used in unsupervised learning, where the model identifies hidden patterns, clusters, or relationships without predefined labels. An "explained dataset" is not a standard machine learning category.
Option D is incorrect because supervised learning does not learn from both labeled and unlabeled datasets as its primary definition. Option E is also incorrect because "explained dataset" is not the correct term.
Therefore, supervised learning learns from a labeled dataset , making A the correct answer.
NEW QUESTION # 24
Which one of the following is a CORRECT benefit for using AI in product development?
Answer: B
NEW QUESTION # 25
Choose the CORRECT benefit of solution architecture.
Answer: B
Explanation:
Solution architecture provides the structured blueprint needed to move from a business or technical concept to a working implementation. It defines how different systems, applications, data flows, technologies, security requirements, and business needs will fit together. Therefore, it gives teams a solid foundation for developing enterprise software solutions.
A well-defined solution architecture is also valuable when projects become large, complex, or distributed across multiple teams and locations. It creates a common understanding of design decisions, integration points, responsibilities, and technical standards, which supports collaboration and long-term sustainability. In addition, solution architecture helps ensure that the final solution meets business expectations, technical requirements, quality standards, scalability needs, security controls, and operational goals.
Since options A, B, and C all describe valid benefits of solution architecture, the most complete and correct answer is E. All of the above .
NEW QUESTION # 26
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