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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. Which metric is commonly used for evaluating Automatic Speech Recognition (ASR) models?

A) CTC Loss
B) F1 Score
C) Word Error Rate (WER)
D) Mean Opinion Score (MOS)

2. In a multimodal machine learning context, how are different modalities usually linked to each other?

A) Different modalities are linked through a shared representation that captures the relationships between the modalities.
B) Different modalities are linked through random connections.
C) Different modalities are linked through separate models that are ensembled by tree-based models.
D) Different modalities are not linked to each other in a multimodal machine learning context.

3. Hyperparameter tuning is used for what purpose in machine learning experimentation?

A) Collecting and preprocessing data to improve the accuracy of the model.
B) Adjusting the weights and biases of a neural network to optimize its performance.
C) Selecting the best ML algorithm for a given task.
D) Selecting the optimal values for non-trainable parameters, such as learning rate or batch size.

4. Which of the following best describes the role of the Hugging Face model repository in ML software development?

A) A platform for sharing and accessing pre-trained models and transformers for natural language processing.
B) A set of NVIDIA SDKs, such as Riva, NeMo, Triton, and ACE, for implementing neural network architectures.
C) A convenient tool for deploying neural networks for production-scale inference similar to Triton Server.
D) A library for customizing large language models like GPT, LLaMA-2, and Falcon using the NeMo framework.

5. Which technique is commonly used to speed up AI model training and inference on hardware accelerators?

A) Dropout
B) Quantization
C) Model enlargement
D) Data augmentation

Solutions: