ABSTRACT
Embark on an exciting journey into the dynamic world of air travel and data science with our innovative project, “Airfare Prices Prediction Using Machine Learning Techniques.” This abstract extends a compelling invitation to students eager to explore the application of machine learning in forecasting airfare prices, unraveling the complexities of the aviation industry through predictive analytics.
In this project, we navigate the intricate landscape of airfare data, employing diverse machine learning techniques to develop a robust prediction model. Students will be introduced to the fundamental concepts of data preprocessing, feature engineering, and the application of regression algorithms, gaining valuable insights into the art of leveraging machine learning for price prediction.
This abstract provides a glimpse into the core principles of our project, showcasing how machine learning algorithms can be trained to analyze historical pricing trends, seasonality, and various factors influencing airfare fluctuations. Through hands-on exploration, students will gain a nuanced understanding of the challenges and innovations in predicting airfare prices, empowering them to contribute to the advancement of intelligent systems within the aviation sector.
