NCA-GENL Question 130
Select 3You are tasked with analyzing a dataset for training a generative AI model under the supervision of a senior team member. During your analysis, you notice several columns with missing values and some features with inconsistent data types. What steps should you take before passing the dataset for training?
- A
Consult the senior team member to determine the appropriate handling of missing values.
- B
Remove all rows with missing values to ensure a clean dataset.
- C
Standardize inconsistent data types to maintain uniformity in the dataset.
- D
Immediately begin training the model to identify any issues during training.
- E
Perform exploratory data analysis (EDA) to identify patterns, correlations, and data distribution.
Show answer and explanation
Correct answers: A, C, E
Explanation
When conducting data analysis for generative AI model training, it is essential to address missing values and inconsistencies in the dataset under the supervision of a senior team member. Consulting with the senior team member ensures proper handling of project-specific issues, while standardizing data types and performing EDA help prepare the data effectively for training.
- A. Correct.
Consulting the senior team member is critical as they can provide guidance on how to handle missing data based on the specific requirements of the model and project.
- B. Incorrect.
Removing all rows with missing values is not always the best approach as it can lead to significant data loss, which may affect the model's performance.
- C. Correct.
Standardizing inconsistent data types is essential for ensuring that the dataset is uniform and compatible with the model training process.
- D. Incorrect.
Immediately beginning training without addressing the missing values or data inconsistencies would likely result in errors or poor model performance.
- E. Correct.
Performing exploratory data analysis (EDA) helps in understanding the dataset better, identifying potential issues, and providing insights for preprocessing steps.