NVIDIA NCA-GENM

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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. In the context of multimodal machine learning, what does 'data fusion' refer to?

A) Combining different modalities of data into a single representation.
B) Evaluating the quality of diverse data types in multimodal machine learning.
C) Removing missing or incomplete information from different modalities.
D) Separating different modalities of data into distinct representations.

2. 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.

3. 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) Linear Regression
C) Decision Trees
D) K-Means Clustering

4. What is the significance of A/B testing in ML software engineering?

A) A/B testing helps in evaluating the performance and effectiveness of different machine learning models.
B) A/B testing is irrelevant in ML software engineering.
C) A/B testing helps in optimizing the hyperparameters of a machine learning model.
D) A/B testing is used to measure the impact of changes in the user interface of a ML application.

5. Which framework is used for conversational AI models development?

A) NVIDIA Metropolis
B) NVIDIA DeepStream
C) NVIDIA NeMo
D) NVIDIA Clara

Solutions: