Amazon Web Services AIF-C01 Test Dumps

A.   Implement moderation APIs.

A.   Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key.

B.   Improves model performance over time

Answer DescriptionExplanation: Ongoing pre-training when fine-tuning a foundation model (FM) improves model performance over time by continuously learning from new data.
Ongoing Pre-Training:
Why Option B is Correct:
Why Other Options are Incorrect:

B.   Increase the epochs

B.   Partial dependence plots (PDPs)

A.   Data augmentation for imbalanced classes

Answer DescriptionExplanation:
Data augmentation for imbalanced classes is the correct technique to address bias in input data affecting image generation.
Data Augmentation for Imbalanced Classes:
Why Option A is Correct:
Why Other Options are Incorrect:

B.   Standardizing information about a model's purpose, performance, and limitations.

Answer DescriptionExplanation: Amazon SageMaker Model Cards provide a standardized way to document important details about an AI model, such as its purpose, performance, intended usage, and known limitations. This enables transparency and compliance while fostering better communication between stakeholders. It does not store models physically or optimize computational requirements. References: AWS SageMaker Model Cards Documentation.

A.   Generative adversarial network (GAN)

Answer DescriptionExplanation:
Generative adversarial networks (GANs) are a type of deep learning model used for generating synthetic data based on existing datasets. GANs consist of two neural networks (a generator and a discriminator) that work together to create realistic data.
Option A (Correct): "Generative adversarial network (GAN)": This is the correct answer because GANs are specifically designed for generating synthetic data that closely resembles the real data they are trained on.
Option B: "XGBoost" is a gradient boosting algorithm for classification and regression tasks, not for generating synthetic data.
Option C: "Residual neural network" is primarily used for improving the performance of deep networks, not for generating synthetic data.
Option D: "WaveNet" is a model architecture designed for generating raw audio waveforms, not synthetic data in general.
AWS AI Practitioner References:
GANs on AWS for Synthetic Data Generation: AWS supports the use of GANs for creating synthetic datasets, which can be crucial for applications like training machine learning models in environments where real data is scarce or sensitive.