最新のNCA-GENM問題集で試験を準備する

What is contrastive learning in the context of multimodal deep learning? Pick the 2 correct responses below.

• A. Contrastive learning is a technique used to manipulate and analyze multimodal data using Generative AI.
• B. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the same objects and decreases the similarity of representations across modalities for different objects.
• C. In a multimodal context, usually, contrastive learning decreases the similarity of representations across modalities for the same objects and increases the similarity of representations across modalities for different objects.
• D. Contrastive learning is a technique used to train deep learning models by comparing similar and dissimilar inputs and optimizing the model to maximize the similarity between representations of similar inputs and minimize the similarity between representations of dissimilar inputs.
• E. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the different objects and decreases the similarity of representations across modalities for same objects.

解説: (JPTestKing メンバーにのみ表示されます)

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 convenient tool for deploying neural networks for production-scale inference similar to Triton Server.
• D. A library for customizing large language models like GPT, LLaMA-2, and Falcon using the NeMo framework.

解説: (JPTestKing メンバーにのみ表示されます)

What is the role of CLIP (Contrastive Language-Image Pretraining) in text-to-image generation?

• A. CLIP provides a common embedding space for both the textual and image modalities.
• B. CLIP is used to generate image captions from textual input.
• C. CLIP is used to enhance datasets through data augmentation for text-to-image generation.
• D. CLIP is used to convert textual input into image embeddings.

解説: (JPTestKing メンバーにのみ表示されます)

What is a common method to reduce the computational cost of deep learning models during inference?

• A. Increasing the batch size.
• B. By replacing activation functions in some neurons with simpler ones.
• C. Pruning weights or neurons.
• D. Adding more convolutional filters.

解説: (JPTestKing メンバーにのみ表示されます)

In machine learning, what is the purpose of data normalization?

• A. To remove irrelevant data from the dataset.
• B. To increase the complexity of the dataset.
• C. To convert data into a specific format for easier analysis.
• D. To reduce the dimensionality of the dataset.

解説: (JPTestKing メンバーにのみ表示されます)