最新的NVIDIA Generative AI Multimodal - NCA-GENM免費考試真題

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 optimizing the hyperparameters of a machine learning model.

D. A/B testing helps in evaluating the performance and effectiveness of different machine learning models.

A. Randomly selecting data points from the training set and calculating the accuracy of the model on these data points.

B. Calculating the model's accuracy from randomly selected data points from the dataset not used during the model's training.

C. Calculating the loss function of the model on the training set.

D. Interviewing the developers of the AI model to assess its performance.

A. Training separate models for each modality and then combining their predictions.

B. Ignoring certain modalities and only using one modality for analysis and prediction.

C. Implementing the model in the early stages of development of the ML solution.

D. Integrating different modalities at the beginning of the model pipeline.

A. Training a deep learning model using the images in the dataset to find outliers and enhancing the quality of MRI scans using image processing techniques.

B. Directly combining MRI scans and radiology reports into a single input stream without preprocessing or modality-specific adjustments.

C. Implementing separate unimodal pipelines for each modality to ensure the data is informative and the model design is accurate.

D. More advanced natural language processing techniques to interpret radiology reports, ignoring the MRI scans' diagnostic value.

A. It can capture more complex patterns and relationships in data.

B. It is more reliable than unimodal learning.

C. It is easier to collect multimodal data than unimodal data.

D. It requires fewer data samples for learning.

A. Content credential

B. Ethical AI development

C. Data encryption

D. Content validity