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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. What is a common method to reduce the computational cost of deep learning models during inference?

A) Pruning weights or neurons.
B) Increasing the batch size.
C) Adding more convolutional filters.
D) By replacing activation functions in some neurons with simpler ones.

2. 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 decreases the similarity of representations across modalities for the same objects and increases the similarity of representations across modalities for different 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 increases the similarity of representations across modalities for the same objects and decreases the similarity of representations across modalities for different objects.
D) 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.
E) 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.

3. How does the batch size influence VRAM consumption during inference with ML models on GPUs?

A) Decreasing the batch size reduces VRAM consumption.
B) The batch size has no impact on VRAM consumption during inference.
C) Increasing the batch size reduces VRAM consumption because more data can be processed in parallel.
D) Increasing or decreasing the batch size has the same impact on VRAM consumption.

4. You are tasked with developing an image processing model using machine learning. You need to classify thousands of labeled images of cats and dogs. Which algorithm is commonly used for image classification?

A) Convolutional Neural Networks (CNN)
B) Decision Trees
C) K-Means Clustering
D) Linear Regression

5. You have a dataset containing information about sales performance for different regions in the last ten years.
Which type of data visualization would be most appropriate to compare the sales performance across regions on a year-by-year basis?

A) Pie chart
B) Line chart
C) Bar chart
D) Scatter plot

Solutions: