NVIDIA NCA-GENM Actual Tests : NVIDIA Generative AI Multimodal

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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. What is the purpose of a kernel in a Convolutional Neural Network (CNN)?

A) To perform convolution operations on input data.
B) To classify the data into different categories.
C) To calculate the loss function.
D) To normalize the input data.

2. Which of the following best describes the role of the Hugging Face model repository in ML software development?

A) A set of NVIDIA SDKs, such as Riva, NeMo, Triton, and ACE, for implementing neural network architectures.
B) A platform for sharing and accessing pre-trained models and transformers for natural language processing.
C) A library for customizing large language models like GPT, LLaMA-2, and Falcon using the NeMo framework.
D) A convenient tool for deploying neural networks for production-scale inference similar to Triton Server.

3. What is the purpose of the cuDNN library?

A) To generate images from English text-prompts using CLIP.
B) To measure GPU usage and other metrics with Prometheus.
C) To implement GPU-accelerated data preparation and feature extraction.
D) To optimize deep neural network computations on NVIDIA GPUs.

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

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

5. What characteristic of autoencoders makes them suitable for anomaly detection?

A) Their capacity to learn a compressed representation of the data.
B) Their function in enhancing the quality of images.
C) Their ability to classify images with high accuracy.
D) Their capability to predict future outcomes based on past data.

Solutions: