A next-word prediction algorithm was built using sentences/text drawn from Twitter, news, and blog data.

This bar chart shows the average pit stop time for each team during the races. Teams are displayed on the y-axis, sorted from the shortest to the longest average time, while the x-axis represents the average time in seconds. The visualization highlights which teams are the most efficient in executing pit stops and identifies performance differences among them. Key Observations: Teams with the shortest average pit stop times are more efficient. Significant differences in efficiency can be observed between the fastest and slower teams. Key Information: Title: Average Pit Stop Time by Team X-Axis: Average Time (seconds) Y-Axis: Teams (sorted by average time)

Histogram: Distribution of Pit Stop Times This histogram visualizes the distribution of pit stop times across all recorded stops in the dataset. The x-axis represents the duration of each pit stop in seconds, while the y-axis indicates the frequency or count of stops within each time interval. Key Observations: The majority of pit stops are concentrated between 0 and 5 seconds, indicating the standard range for most teams. A few stops took significantly longer, creating noticeable outliers in the data. This chart helps identify patterns in pit stop efficiency and highlights any unusually long or short stops. Key Information: Title: Distribution of Pit Stop Times X-Axis: Pit Stop Time (seconds) Y-Axis: Frequency (number of stops)

cluster plot by region

Bivariate gamma distribution plot using synthetic data generation

bar chart for AI/ML approaches per region

AI/ML approaches per region

scatter plot