NVIDIA Generative AI Multimodal - NCA-GENM

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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

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

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

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

3. In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?

A) Support vector machine (SVM)
B) K-means clustering
C) Decision tree
D) Generative adversarial network (GAN)

4. Which visualization technique is suitable for representing the distribution of performance scores for different multimodal ML models over different modalities?

A) Heatmap
B) Pie chart
C) Box plot
D) Histogram

5. What does 'kernel fusion' refer to in the context of AI model optimization?

A) Combining multiple kernels into a single kernel for faster computation.
B) Applying multiple layers of kernels to improve model accuracy.
C) Optimizing model inference by reducing the number of computations by pruning.
D) Using kernel functions to optimize model hyperparameters.

Solutions: