NCA-GENM Question 91
Select 3You are developing a generative AI multimodal model that incorporates text, image, and audio data from different sources. Before proceeding to model training, you need to ensure the data is properly managed and preprocessed. Which of the following steps are essential to prepare the dataset for training?
- A
Normalize the data to bring all features to a similar scale.
- B
Ensure all text data is converted to lowercase to maintain consistency.
- C
Remove irrelevant data and noise from all modalities.
- D
Use a single preprocessing pipeline for all modalities to save time.
- E
Handle missing values by replacing them with defaults or interpolating where appropriate.
Show answer and explanation
Correct answers: A, C, E
Explanation
Data management and preprocessing are critical for building a robust generative AI multimodal model. Normalizing the data ensures numerical stability, removing irrelevant data enhances dataset quality, and handling missing values prevents errors during training. Each modality requires unique preprocessing techniques, so a single pipeline cannot handle all modalities effectively, and text-specific transformations like converting to lowercase depend on the specific task.
- A. Correct.
Normalization is an essential preprocessing step to ensure that the scale of features does not disproportionately affect the model's learning process.
- B. Incorrect.
While converting text to lowercase may help in certain NLP tasks, it is not universally required and depends on the specific use case.
- C. Correct.
Removing irrelevant data and noise is critical for improving the quality of the dataset and ensuring the model focuses on meaningful patterns.
- D. Incorrect.
Using a single preprocessing pipeline for all modalities is not feasible because each modality (text, image, and audio) requires different preprocessing techniques.
- E. Correct.
Handling missing values is vital to ensure the dataset is complete and does not introduce biases or errors during training.