Exam NCA-GENL Topic 8 Question 31 Discussion

Actual exam question for NVIDIA's NCA-GENL exam
Question #: 31
Topic #: 8

What is the primary purpose of applying various image transformation techniques (e.g., flipping, rotation, zooming) to a dataset?

A. To simplify the model's architecture, making it easier to interpret the results. B. To artificially expand the dataset's size and improve the model's ability to generalize. C. To ensure perfect alignment and uniformity across all images in the dataset. D. To reduce the computational resources required for training deep learning models.

Suggested Answer: B Vote an answer

Image transformation techniques such as flipping, rotation, and zooming are forms of data augmentation used to artificially increase the size and diversity of a dataset. NVIDIA's Deep Learning AI documentation, particularly for computer vision tasks using frameworks like DALI (Data Loading Library), explains that data augmentation improves a model's ability to generalize by exposing it to varied versions of the training data, thus reducing overfitting. For example, flipping an image horizontally creates a new training sample that helps the model learn invariance to certain transformations. Option A is incorrect because transformations do not simplify the model architecture. Option C is wrong, as augmentation introduces variability, not uniformity. Option D is also incorrect, as augmentation typically increases computational requirements due to additional data processing.
References:
NVIDIA DALI Documentation: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/index.html

by Wilbur at Jun 29, 2025, 03:15 AM

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