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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

Question 1

What is contrastive learning in the context of multimodal deep learning? Pick the 2 correct responses below.

A. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the different objects and decreases the similarity of representations across modalities for same objects.
B. Contrastive learning is a technique used to manipulate and analyze multimodal data using Generative AI.
C. In a multimodal context, usually, contrastive learning decreases the similarity of representations across modalities for the same objects and increases the similarity of representations across modalities for different objects.
D. Contrastive learning is a technique used to train deep learning models by comparing similar and dissimilar inputs and optimizing the model to maximize the similarity between representations of similar inputs and minimize the similarity between representations of dissimilar inputs.
E. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the same objects and decreases the similarity of representations across modalities for different objects.

Question 2

What is the purpose of a kernel in a Convolutional Neural Network (CNN)?

A. To perform convolution operations on input data.
B. To normalize the input data.
C. To classify the data into different categories.
D. To calculate the loss function.

Question 3

How does CLIP understand the content of both text and images?

A. Using contrastive learning to match images with text descriptions.
B. By translating images into text and comparing them with the prompt.
C. Through a database of predefined images with their descriptions.
D. By converting text and images into a frequency domain for comparison.

Question 4

Which of the following best describes the role of machine learning in handling multimodal data?

A. To reduce the amount of data needed for accurate predictions.
B. To focus on textual data analysis.
C. To eliminate the need for human intervention in data analysis.
D. To enable models to learn from and interpret diverse data types.

Question 5

What is the correct order of steps in an ML project?

A. Model evaluation, Data collection, Data preprocessing, Model training
B. Model evaluation, Data preprocessing, Model training, Data collection
C. Data collection, Data preprocessing, Model training, Model evaluation
D. Data preprocessing, Data collection, Model training, Model evaluation

Solutions: