NCA-GENL試験無料問題集（97題）「NVIDIA Generative AI LLMs 認定」

出題：1

Why do we need positional encoding in transformer-based models?

A. To increase the throughput of the model.

B. To reduce the dimensionality of the input data.

C. To represent the order of elements in a sequence.

D. To prevent overfitting of the model.

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：2

What is the Open Neural Network Exchange (ONNX) format used for?

A. Sharing neural network literature

B. Representing deep learning models

C. Reducing training time of neural networks

D. Compressing deep learning models

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：3

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

A. To add information about the order of each token in the input sequence.

B. To encode the semantic meaning of each token in the input sequence.

C. To encode the importance of each token in the input sequence.

D. To remove redundant information from the input sequence.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：4

Which tool would you use to select training data with specific keywords?

A. Tableau dashboard

B. JSON parser

C. Regular expression filter

D. ActionScript

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：5

Which of the following principles are widely recognized for building trustworthy AI? (Choose two.)

A. Scalability

B. Nondiscrimination

C. Privacy

D. Low latency

E. Conversational

正解：B,C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：6

When designing an experiment to compare the performance of two LLMs on a question-answering task, which statistical test is most appropriate to determine if the difference in their accuracy is significant, assuming the data follows a normal distribution?

A. Mann-Whitney U test

B. Paired t-test

C. Chi-squared test

D. ANOVA test

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：7

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

A. Inspecting, cleansing, and transforming data

B. Data visualization and analysis

C. Performing GPU-accelerated machine learning tasks

D. Training deep learning models

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：8

You are in need of customizing your LLM via prompt engineering, prompt learning, or parameter-efficient fine-tuning. Which framework helps you with all of these?

A. NVIDIA DALI

B. NVIDIA NeMo

C. NVIDIA TensorRT

D. NVIDIA Triton

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：9

When fine-tuning an LLM for a specific application, why is it essential to perform exploratory data analysis (EDA) on the new training dataset?

A. To determine the optimum number of layers in the neural network

B. To uncover patterns and anomalies in the dataset

C. To select the appropriate learning rate for the model

D. To assess the computing resources required for fine-tuning

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：10

What is the correct order of steps in an ML project?

A. Model evaluation, Data preprocessing, Model training, Data collection

B. Data preprocessing, Data collection, Model training, Model evaluation

C. Model evaluation, Data collection, Data preprocessing, Model training

D. Data collection, Data preprocessing, Model training, Model evaluation

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

NCA-GENL試験無料問題集「NVIDIA Generative AI LLMs 認定」