Online Access Free NCA-GENL Exam Questions

You are working on developing an application to classify images of animals and need to train a neural model.
However, you have a limited amount of labeled data. Which technique can you use to leverage the knowledge from a model pre-trained on a different task to improve the performance of your new model?

• A.Transfer learning
• B.Early stopping
• C.Random initialization
• D.Dropout

What is the purpose of the NVIDIA NGC catalog?

• A.To provide a platform for testing and debugging software applications.
• B.To provide a curated collection of GPU-optimized AI and data science software.
• C.To provide a platform for developers to collaborate and share software development projects.
• D.To provide a marketplace for buying and selling software development tools and resources.

Which of the following tasks is a primary application of XGBoost and cuML?

• A.Performing GPU-accelerated machine learning tasks
• B.Training deep learning models
• C.Data visualization and analysis
• D.Inspecting, cleansing, and transforming data

Imagine you are training an LLM consisting of billions of parameters and your training dataset is significantly larger than the available RAM in your system. Which of the following would be an alternative?

• A.Using a memory-mapped file that allows the library to access and operate on elements of the dataset without needing to fully load it into memory.
• B.Discarding the excess of data and pruning the dataset to the capacity of the RAM, resulting in reduced latency during inference.
• C.Using the GPU memory to extend the RAM capacity for storing the dataset and move the dataset in and out of the GPU, using the PCI bandwidth possibly.
• D.Eliminating sentences that are syntactically different by semantically equivalent, possibly reducing the risk of the model hallucinating as it is trained to get to the point.

In the transformer architecture, what is the purpose of positional encoding?

• A.To encode the importance of each token in the input sequence.
• B.To add information about the order of each token in the input sequence.
• C.To remove redundant information from the input sequence.
• D.To encode the semantic meaning of each token in the input sequence.