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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. Assume you need to implement a multimodal pipeline to diagnose brain cancer type using MRI scans and their corresponding radiology reports. What do you need to include in the ablation study?

A) Directly combining MRI scans and radiology reports into a single input stream without preprocessing or modality-specific adjustments.
B) More advanced natural language processing techniques to interpret radiology reports, ignoring the MRI scans' diagnostic value.
C) 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.
D) Implementing separate unimodal pipelines for each modality to ensure the data is informative and the model design is accurate.

2. You are developing a ML model for image classification. You have a dataset with 10,000 images of cats, dogs and birds. Which of the following ML models would be the most appropriate choice for this task?

A) Convolutional Neural Network (CNN)
B) K-Means Clustering
C) Logistic Regression
D) Linear Regression

3. What role does 'late fusion' play in multimodal machine learning?

A) It refers to the process of combining multiple modalities at the preprocessing stage.
B) It refers to the process of combining multiple modalities at the training stage.
C) It refers to the process of combining multiple modalities at the decision level.
D) It refers to the process of combining multiple modalities at the feature level.

4. Which visualization technique is suitable for representing the distribution of performance scores for different multimodal ML models over different modalities?

A) Pie chart
B) Box plot
C) Histogram
D) Heatmap

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

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

Solutions: