Google Professional Machine Learning Engineer
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In the context of machine learning, you are tasked with analyzing a dataset that records the daily temperature and humidity levels over a year to identify any trends or patterns. The dataset is large, with measurements taken every hour. Your goal is to visualize this data to best communicate the trends over time to stakeholders who are not technically savvy. Considering the need for clarity, simplicity, and effectiveness in trend visualization, which type of plot would you choose? (Choose one correct option)
In the context of machine learning, you are tasked with analyzing a dataset that records the daily temperature and humidity levels over a year to identify any trends or patterns. The dataset is large, with measurements taken every hour. Your goal is to visualize this data to best communicate the trends over time to stakeholders who are not technically savvy. Considering the need for clarity, simplicity, and effectiveness in trend visualization, which type of plot would you choose? (Choose one correct option)
Explanation:
A line plot is the most suitable for visualizing trends over time as it connects data points with a line, clearly showing how a variable changes over a period. This makes it easy to spot patterns, trends, and seasonal variations. Given the large dataset with hourly measurements, aggregating the data to daily averages and using a line plot would effectively communicate the trends to non-technical stakeholders. Incorrect Options: - Box plot: Best for visualizing the distribution of a numerical variable, highlighting quartiles, median, and outliers. - Scatter plot: Ideal for examining the relationship between two numerical variables. - Histogram: Used to visualize the distribution of a single numerical variable. Therefore, for identifying trends over time in a large dataset intended for non-technical stakeholders, a line plot is the optimal choice.