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 working with a large dataset and want to visualize the distribution of a continuous variable. Which type of data visualization would be most appropriate?

A) Pie chart
B) Bar chart
C) Line chart
D) Histogram chart

2. What are some methods to overcome limited throughput between CPU and GPU?

A) Increase the clock speed of the CPU.
B) Increase the number of CPU cores.
C) Upgrade the GPU to a higher-end model.
D) Using techniques like memory pooling.

3. You are evaluating the performance of an AI model for facial recognition. What is an important consideration when evaluating the model for bias?

A) The model's compatibility with different operating systems.
B) The model's accuracy in recognizing individuals of different races.
C) The model's processing speed in recognizing faces of different races.
D) The model's ability to recognize various facial expressions.

4. Which technique is commonly used to speed up AI model training and inference on hardware accelerators?

A) Model enlargement
B) Data augmentation
C) Dropout
D) Quantization

5. In experimentation, how does data augmentation contribute to improving model accuracy?

A) It has no impact on model accuracy and is primarily used for data visualization purposes.
B) It improves the interpretability of the model by providing additional insights into the data.
C) It helps in increasing the size of the dataset, leading to better generalization of the model.
D) It reduces the complexity of the model, making it easier to train and evaluate.

Solutions: