EDA on Flight Prediction
"EDA on Flight Prediction" is a project that focuses on exploratory data analysis of flight data to predict the prices of flights between different cities. The project involves the use of machine learning algorithms to build a model that predicts the price of a flight based on historical data.
The project includes a python notebook that walks through the data cleaning and preprocessing steps, feature engineering, model building, and evaluation. The notebook uses Python libraries such as pandas, numpy, matplotlib, and scikit-learn for data manipulation and modeling.
The project also includes the original dataset in CSV format and a README file that provides instructions on how to reproduce the analysis. Users can clone the repository and run the notebook on their local machine or a cloud-based platform such as Google Colab.
The project is useful for data scientists, researchers, and anyone interested in the travel industry. The insights gained from the analysis can inform pricing strategies, marketing campaigns, and customer preferences. The project also demonstrates how machine learning algorithms can be used to solve real-world problems and make predictions based on historical data.