Predict the fare on airline tickets
The purpose of this project is to help airline companies to predict the price of a ticket based on all the information surrounding it. This will help the airline companies to boost their revenue which is their ultimate aim. The price is an important factor as nowadays price changes due to seat availability and demand.
This Functional and Technical Requirements Document outlines the functional requirements of flight fare prediction. The project will determine which airplane has lowest ticket. The project will also include a graphical representation of different model.
This is the flight fare prediction in which we will find out the price of a ticket. We will Start the data analysis, data wrangling, data preprocessing, then perform many machine learning algorithms to determine the accurate results.
Nowadays the price changes abruptly. The price of a flight may change within an hour as according to Robert W. Mann “Today, airlines price tickets as much as the customer and market will bear,” so this project flight fare prediction will help companies to keep an eye on all the factors and keep prices that will maximize their revenue.
The flight fare prediction is a technology-based solution for airline companies to determine their prices. Following are the functional requirement:
- Data cleaning
- Data Handling
- Features detection from data
- Machine Learning algorithm
- Python (including libraries like Pandas, matplotlib etc.)
- Jupyter notebook
In this project I will use the dataset of MachineHack that is given on Kaggle. The dataset link is given below: Dataset Link