Amazon AIF-C01 Exam | AIF-C01 Top Questions - High-effective Company for AIF-C01: AWS Certified AI Practitioner Exam

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Amazon AWS Certified AI Practitioner Sample Questions (Q67-Q72):

NEW QUESTION # 67
An AI practitioner is building a model to generate images of humans in various professions. The AI practitioner discovered that the input data is biased and that specific attributes affect the image generation and create bias in the model.
Which technique will solve the problem?

A. Watermark detection for images
B. Data augmentation for imbalanced classes
C. Retrieval Augmented Generation (RAG)
D. Model monitoring for class distribution

Answer: B

NEW QUESTION # 68
A company manually reviews all submitted resumes in PDF format. As the company grows, the company expects the volume of resumes to exceed the company's review capacity. The company needs an automated system to convert the PDF resumes into plain text format for additional processing.
Which AWS service meets this requirement?

A. Amazon Transcribe
B. Amazon Textract
C. Amazon Lex
D. Amazon Personalize

Answer: B

Explanation:
Amazon Textract is a service that automatically extracts text and data from scanned documents, including PDFs. It is the best choice for converting resumes from PDF format to plain text for further processing.
* Amazon Textract:
* Extracts text, forms, and tables from scanned documents accurately.
* Ideal for automating the process of converting PDF resumes into plain text format.
* Why Option A is Correct:
* Automation of Text Extraction: Textract is designed to handle large volumes of documents and convert them into machine-readable text, perfect for the company's need.
* Scalability and Efficiency: Supports scalability to handle a growing volume of resumes as the company expands.
* Why Other Options are Incorrect:
* B. Amazon Personalize: Used for creating personalized recommendations, not for text extraction.
* C. Amazon Lex: A service for building conversational interfaces, not for processing documents.
* D. Amazon Transcribe: Used for converting speech to text, not for extracting text from documents.

NEW QUESTION # 69
A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output.
Which ML algorithm meets these requirements?

A. Logistic regression
B. Neural networks
C. Linear regression
D. Decision trees

Answer: D

Explanation:
Decision trees are an interpretable machine learning algorithm that clearly documents the decision-making process by showing how each input feature affects the output. This transparency is particularly useful when explaining how the model arrives at a certain decision, making it suitable for classifying genes into categories.
* Option A (Correct): "Decision trees": This is the correct answer because decision trees provide a clear and interpretable representation of how input features influence the model's output, making it ideal for understanding the inner mechanisms affecting predictions.
* Option B: "Linear regression" is incorrect because it is used for regression tasks, not classification.
* Option C: "Logistic regression" is incorrect as it does not provide the same level of interpretability in documenting decision-making processes.
* Option D: "Neural networks" is incorrect because they are often considered "black boxes" and do not easily explain how they arrive at their outputs.
AWS AI Practitioner References:
* Interpretable Machine Learning Models on AWS: AWS supports using interpretable models, such as decision trees, for tasks that require clear documentation of how input data affects output decisions.

NEW QUESTION # 70
A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy.
Which additional data does the company need to meet these requirements?

A. Pairs of chatbot responses and correct user intents
B. Pairs of user messages and correct chatbot responses
C. Pairs of user messages and correct user intents
D. Pairs of user intents and correct chatbot responses

Answer: C

Explanation:
Few-shot learning involves providing a model with a few examples (shots) to learn from. For improving intent detection accuracy in a chatbot using a large language model (LLM), the data should consist of pairs of user messages and their corresponding correct intents.
* Few-shot Learning for Intent Detection:
* Few-shot learning aims to enable the model to learn from a small number of examples. For intent detection, the model needs to understand the relationship between user messages and the intended action or meaning.
* Providing examples of user messages and the correct user intents allows the model to learn patterns in the phrasing or language that corresponds to each intent.
* Why Option C is Correct:
* User Messages and Intents: These examples directly teach the model how to map a user's input to the appropriate intent, which is the goal of intent detection in chatbots.
* Improves Accuracy: By using few-shot learning with these examples, the model can generalize better from limited data, improving intent detection.
* Why Other Options are Incorrect:
* A. Pairs of chatbot responses and correct user intents: Incorrect because it does not focus on user input but rather on outputs.
* B. Pairs of user messages and correct chatbot responses: This would be useful for response generation, not intent detection.
* D. Pairs of user intents and correct chatbot responses: Again, this is not aligned with detecting intents but with generating responses.

NEW QUESTION # 71
Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?

A. Assess the color accuracy of images processed by the model.
B. Measure the model's accuracy against a predefined benchmark dataset.
C. Count the number of layers in the neural network.
D. Calculate the total cost of resources used by the model.

Answer: B

NEW QUESTION # 72
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Amazon AIF-C01 Exam | AIF-C01 Top Questions - High-effective Company for AIF-C01: AWS Certified AI Practitioner Exam

Free PDF 2025 AIF-C01: Unparalleled AWS Certified AI Practitioner Top Questions

Amazon AWS Certified AI Practitioner Sample Questions (Q67-Q72):

Top AIF-C01 Top Questions | High Pass-Rate AIF-C01 Valid Dumps Demo: AWS Certified AI Practitioner