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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

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

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

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

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

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

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

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

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

5. 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)

Solutions: