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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Experimentation | 25% | - A/B testing - Experimental design - Model evaluation and comparison - Hypothesis testing |
| Trustworthy AI | 5% | - Ensuring fairness and transparency - Ethical considerations in AI development |
| Performance Optimization | 10% | - Techniques for optimizing AI performance - Monitoring and improving system efficiency |
| Data Analysis & Visualization | 10% | - Data preprocessing and feature engineering - Visualization techniques for multimodal data |
| Core ML & AI Knowledge | 20% | - Key algorithms and techniques - Basic concepts and terminology |
| Multimodal Data | 15% | - Handling and integrating text, image, and audio data - Applications and use cases |
| Software Development & Engineering | 15% | - Python libraries for multimodal AI - Integration and deployment of multimodal AI systems |
NVIDIA Generative AI Multimodal Sample Questions:
In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?
- A. Generative adversarial network (GAN)
- B. Decision tree
- C. Support vector machine (SVM)
- D. K-means clustering
Correct Answer: A 🗳️
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In the context of multimodal machine learning, what does 'data fusion' refer to?
- A. Evaluating the quality of diverse data types in multimodal machine learning.
- B. Separating different modalities of data into distinct representations.
- C. Combining different modalities of data into a single representation.
- D. Removing missing or incomplete information from different modalities.
Correct Answer: C 🗳️
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Which of the following best describes the purpose of GAN (Generative Adversarial Networks)?
- A. To optimize search algorithms for faster data retrieval.
- B. To produce new data that is similar to the training data.
- C. To classify and categorize data based on patterns and features.
- D. To optimize decision-making processes based on historical data.
Correct Answer: B 🗳️
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What is the correct order of steps in an ML project?
- A. Data preprocessing, Data collection, Model training, Model evaluation
- B. Model evaluation, Data collection, Data preprocessing, Model training
- C. Data collection, Data preprocessing, Model training, Model evaluation
- D. Model evaluation, Data preprocessing, Model training, Data collection
Correct Answer: C 🗳️
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During the process of data cleansing, which of the following steps is NOT typically performed?
- A. Identifying and handling missing values
- B. Removing duplicates
- C. Transforming data into a different format
- D. Collecting additional data
Correct Answer: D 🗳️
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