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NVIDIA NCA-GENM Exam Overview:

NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

Question 1

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

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

Question 2

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

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

Question 3

In convolutional neural networks, we may use padding in both convolution and transposed convolution.
Which two (2) statements accurately describe padding in convolution and transposed convolution? Pick the 2 correct responses below.

A. Padding in convolution increases the spatial dimensions of the input feature map, while padding in transposed convolution decreases the spatial dimensions of the output feature maps.
B. Padding in convolution and transposed convolution serve the same purpose of reducing the convolutional neural network's memory requirement and computational cost of the convolutional neural network.
C. Padding in convolution enables convolution operations on the boundary pixels of the input. In transposed convolution, it removes rows and columns along the perimeter of the input after it is expanded with stride.
D. Padding in convolution is used only when the input image is smaller than the filter size, while padding in transposed convolution is used only when the input image is larger than the filter size.
E. In a convolution operation, padding is added to the output after it has been expanded with the stride. On the other hand, in a transposed convolution operation, padding is added to the input before it is expanded with stride.

Question 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. Logistic Regression
C. Linear Regression
D. K-Means Clustering

Question 5

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. 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.
D. 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.
E. 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.

Solutions: