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The project by Group 29 focuses on creating a machine learning prediction model for cheap flight tickets. The airline industry uses complex dynamic pricing strategies, unlike fixed pricing in road transport. Airlines adjust ticket prices frequently based on various parameters, leading to fluctuations in costs for the same route at different times. Key factors influencing these price changes include the number of seats available, among others. The goal of the project is to analyze these dynamic pricing patterns to provide better insights for consumers seeking affordable flight options.