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Group 29's Pioneer project focuses on developing a machine learning prediction model for cheap flight tickets. The airline industry employs complex dynamic pricing strategies that lead to fluctuating ticket prices, unlike fixed pricing in road transport. Prices can vary significantly within short time frames based on various parameters. Key features influencing ticket pricing include the number of available seats and other dynamic factors that dictate price changes. The project aims to leverage these features to predict and optimize flight ticket prices effectively.