A company is analyzing financial transaction records. The company categorizes the records as either personal or business. The company inserts the categories into the transaction records.
Which data preparation step does this describe?
A. Data encoding
B. Data labeling
C. Data normalization
D. Data balancing
Show Answer
Correct Answer: B
Explanation: Assigning categories such as 'personal' or 'business' to transaction records is the data labeling step. Labeling adds target classes or annotations to data, typically for supervised machine learning. Data encoding transforms feature representations, normalization rescales values, and balancing adjusts class distributions.
Question 175
A company receives a large amount of unstructured user feedback in text format. The company wants to analyze the sentiment of the user feedback. Which solution will meet these requirements?
A. Use a large language model (LLM) to perform natural language processing (NLP) for sentiment analysis.
B. Use a regression algorithm to classify the feedback based on predefined categories. Then, analyze user sentiment.
C. Use a recommendation engine algorithm to detect user sentiment.
D. Use a time series algorithm to predict user sentiment based on past feedback.
Show Answer
Correct Answer: A
Explanation: Sentiment analysis on large amounts of unstructured text is a natural language processing task. Large language models are well suited to understanding free-form text and classifying sentiment (such as positive, negative, or neutral). Regression predicts continuous numeric values, recommendation engines suggest items, and time series models forecast temporal data rather than analyze text sentiment.
Question 176
HOTSPOT
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An ecommerce company is developing a generative AI solution to create personalized product recommendations for its application users. The company wants to track how effectively the AI solution increases product sales and user engagement in the application.
Select the correct business metric from the following list for each business goal. Each business metric should be selected one time.
Show Answer
Correct Answer: Click-through rate (CTR)
Average order value (AOV)
Retention rate
Explanation: CTR measures engagement with recommendations, AOV measures the value of purchases, and retention rate measures users returning to the platform.
Question 177
A company is developing an ML application. The application must automatically group similar customers and products based on their characteristics. Which ML strategy should the company use to meet these requirements?
A. Unsupervised learning
B. Supervised learning
C. Reinforcement learning
D. Semi-supervised learning
Show Answer
Correct Answer: A
Explanation: The requirement is to automatically group similar customers and products based on their characteristics without mention of labeled training data. This is a clustering task, which is a classic application of unsupervised learning.
Question 178
A company has created multiple ML models. The company needs a solution for storing, managing, and versioning the models.
Which AWS service or feature meets these requirements?
A. AWS Audit Manager
B. Amazon SageMaker Model Monitor
C. Amazon SageMaker Model Registry
D. Amazon SageMaker Canvas
Show Answer
Correct Answer: C
Explanation: Amazon SageMaker Model Registry is designed to store, organize, manage, and version machine learning models, supporting model lifecycle management. AWS Audit Manager is for compliance auditing, SageMaker Model Monitor monitors deployed model quality, and SageMaker Canvas is a no-code ML tool rather than a model registry.
Question 179
A company is developing a generative AI application to automatically generate product descriptions for an ecommerce website. The product descriptions must consist of paragraphs of text that are consistent in style and tone. The application must generate thousands of unique descriptions each day.
Which type of generative model will meet these requirements?
A. A variational autoencoder (VAE) model
B. A transformer-based model
C. A diffusion model
D. A generative adversarial network (GAN) model
Show Answer
Correct Answer: B
Explanation: Transformer-based models are the standard architecture for generating coherent natural language, including multi-paragraph product descriptions with consistent style and tone at scale. VAEs and GANs are not the primary choice for high-quality text generation, and diffusion models are predominantly used for image and other continuous data generation rather than production text generation.
Question 180
A company is developing an ML model to predict heart disease risk. The model uses patient data, such as age, cholesterol, blood pressure, smoking status, and exercise habits. The dataset includes a target value that indicates whether a patient has heart disease.
Which ML technique will meet these requirements?
A. Unsupervised learning
B. Supervised learning
C. Reinforcement learning
D. Semi-supervised learning
Show Answer
Correct Answer: B
Explanation: The dataset includes labeled examples with a target value indicating whether each patient has heart disease. Learning a mapping from input features (age, cholesterol, blood pressure, smoking status, exercise habits) to a known label is supervised learning. Because the target is a categorical yes/no outcome, this is a classification task within supervised learning.
Question 181
HOTSPOT
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Select the correct prompt engineering technique from the following list for each description. Select each prompt engineering technique one time or not at all.
Explanation: Few-shot uses several examples, chain-of-thought asks for step-by-step reasoning, and zero-shot performs the task without examples.
Question 182
An AI practitioner notices a large language model (LLM) is generating different responses for the same input across multiple invocations.
Which risk of AI does this describe?
A. Hallucinations
B. Nondeterminism
C. Accuracy
D. Multimodality
Show Answer
Correct Answer: B
Explanation: The described behavior is nondeterminism: the model can generate different outputs for the same prompt across different invocations due to probabilistic decoding or system variability. Hallucinations refer to fabricated or false content, accuracy concerns correctness, and multimodality refers to handling multiple data modalities.
Question 183
A company wants to extract key insights from large policy documents to increase employee efficiency.
Which generative AI strategy meets this requirement?
A. Regression
B. Clustering
C. Summarization
D. Classification
Show Answer
Correct Answer: C
Explanation: Summarization is the generative AI capability designed to condense long documents into shorter versions while preserving the key points and insights, making large policy documents easier and faster for employees to understand.
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