Uber Trips Analysis: Machine Learning Clustering for Analysing Travel Patterns

Key Points

• The research aims to evaluate travel patterns through machine learning clustering techniques applied to Uber trips.
• Utilized machine learning algorithms for clustering analysis
• Gathered trip data from Uber services
• Conducted data analyses to identify travel patterns
• Identified distinct travel patterns among Uber trips
• Demonstrated the effectiveness of machine learning in analyzing travel data
• Provided insights that could enhance urban planning and transport services

Abstract