NCA-GENM exam dumps

NCA-GENM practice question 70 of 228

NVIDIA-Certified Associate - Generative AI Multimodal. Associate level, NVIDIA. Free question with the correct answer and a full explanation.

NCA-GENM Question 70

Single answer

You have been tasked with creating a visualization to convey the results of a sentiment analysis model applied to a large dataset of customer reviews. The stakeholders want to quickly understand the distribution of positive, neutral, and negative sentiments at a glance. Which type of visualization would be the most appropriate for this task?

  1. A

    A pie chart displaying the proportion of positive, neutral, and negative sentiments.

  2. B

    A line chart showing the change in sentiment scores over time.

  3. C

    A scatter plot comparing the length of reviews to their sentiment scores.

  4. D

    A heatmap showing the frequency of key sentiment-related words in reviews.

Show answer and explanation

Correct answer: A

Explanation

The goal is to create a visualization that effectively communicates the distribution of sentiment categories (positive, neutral, negative) in the dataset. A pie chart is the most suitable option because it clearly represents proportions, making it easy for stakeholders to quickly grasp the sentiment breakdown. Other visualization types, while valuable in other contexts, do not align with the specific requirements of this task.

  • A. Correct.

    A pie chart is an ideal choice for showing proportions or percentages within a dataset, making it easy to understand the distribution of positive, neutral, and negative sentiments at a glance.

  • B. Incorrect.

    A line chart is better suited for visualizing trends over time, which is not the primary goal in this scenario.

  • C. Incorrect.

    A scatter plot is useful for identifying relationships or correlations between two continuous variables, but it does not effectively convey proportions or distributions of sentiments.

  • D. Incorrect.

    A heatmap is excellent for showing patterns or densities in data, such as word frequencies, but it does not directly address the need for visualizing sentiment distribution.

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