NCA-GENL Question 95
Select 3You are tasked with assisting a senior team member in analyzing a dataset intended for training a large language model (LLM). During the analysis phase, the senior team member asks you to identify potential issues that could affect the training process. Which of the following actions would be appropriate under their supervision?
- A
Check for missing or incomplete data entries in the dataset.
- B
Evaluate the dataset for biases or imbalances in the distribution of data categories.
- C
Generate synthetic data to address gaps in the dataset without consulting the senior team member.
- D
Visualize data patterns and correlations to better understand the dataset’s structure.
- E
Perform hyperparameter tuning for the LLM model before dataset preparation is complete.
Show answer and explanation
Correct answers: A, B, D
Explanation
Under the supervision of a senior team member, your role in data analysis is to ensure the dataset is clean, balanced, and well-understood before proceeding to further stages of the AI/ML pipeline. Actions like identifying missing data, evaluating biases, and visualizing patterns are critical components of this process. However, tasks such as generating synthetic data or performing hyperparameter tuning fall outside the data analysis phase and require senior approval or are premature at this stage.
- A. Correct.
Correct: Identifying missing or incomplete data is a fundamental step in data analysis and ensures that the dataset is clean and reliable for model training.
- B. Correct.
Correct: Evaluating biases or imbalances is crucial for training fair and effective LLMs, as these issues can significantly impact model performance and ethical considerations.
- C. Incorrect.
Incorrect: Generating synthetic data without senior supervision is outside the scope of this task, as it involves making substantial changes to the dataset that require approval and expertise.
- D. Correct.
Correct: Visualizing data patterns helps in understanding the structure and relationships within the dataset, a key step in effective data analysis.
- E. Incorrect.
Incorrect: Hyperparameter tuning is related to model training and should not be performed before the dataset is fully prepared and analyzed.