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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

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

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

2. What role does 'late fusion' play in multimodal machine learning?

A) It refers to the process of combining multiple modalities at the preprocessing stage.
B) It refers to the process of combining multiple modalities at the training stage.
C) It refers to the process of combining multiple modalities at the decision level.
D) It refers to the process of combining multiple modalities at the feature level.

3. In large-language models, what is the purpose of the attention mechanism?

A) To determine the order in which words are generated.
B) To assign weights to each word in the input sequence.
C) To capture the order of the words in the input sequence.
D) To measure the importance of the words in the output sequence.

4. You are developing a ML model for image classification. You have a dataset with 10,000 images of cats, dogs and birds. Which of the following ML models would be the most appropriate choice for this task?

A) Convolutional Neural Network (CNN)
B) K-Means Clustering
C) Logistic Regression
D) Linear Regression

5. In the transformer architecture, what is the purpose of positional encoding?

A) To add information about the order of each token in the input sequence.
B) To remove redundant information from the input sequence.
C) To encode the importance of each token in the input sequence.
D) To encode the semantic meaning of each token in the input sequence.

Solutions: