AIF-C01 perp training & AIF-C01 testking vce & AIF-C01 valid torrent
AIF-C01 perp training & AIF-C01 testking vce & AIF-C01 valid torrent
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Tags: AIF-C01 New Dumps Free, AIF-C01 Braindumps, Sample AIF-C01 Questions, AIF-C01 Latest Study Notes, AIF-C01 Exam Questions Pdf
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Amazon AIF-C01 Braindumps - Sample AIF-C01 Questions
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Amazon AWS Certified AI Practitioner Sample Questions (Q44-Q49):
NEW QUESTION # 44
A company wants to assess the costs that are associated with using a large language model (LLM) to generate inferences. The company wants to use Amazon Bedrock to build generative AI applications.
Which factor will drive the inference costs?
- A. Amount of data used to train the LLM
- B. Temperature value
- C. Number of tokens consumed
- D. Total training time
Answer: C
NEW QUESTION # 45
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. Linear regression
- C. Decision trees
- D. Neural networks
Answer: C
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 # 46
A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.
Which business objective should the company use to evaluate the effect of the LLM chatbot?
- A. Website engagement rate
- B. Corporate social responsibility
- C. Regulatory compliance
- D. Average call duration
Answer: D
NEW QUESTION # 47
A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals.
Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?
- A. Moderation logs
- B. Content moderation guidelines
- C. User-generated content
- D. Benchmark datasets
Answer: D
NEW QUESTION # 48
A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source.
Which solution meets these requirements?
- A. Develop an anomaly detection system.
- B. Create a fraud forecasting system.
- C. Build a speech recognition system.
- D. Create a natural language processing (NLP) named entity recognition system.
Answer: A
NEW QUESTION # 49
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