Travelling is one of the most entertaining things that everybody wants to avoid city crowds. Going to another island with a unique nature brings a new perspective about new things. The Indian, one of the most entertaining cities with its uniqueness, brings a lot of wonderful islands. Based on Outlook of the Indian travel Industry, The tourism industry contributes around $98 billion in 2018 and expected to arise in the next period. This trend brings India as one of the immense potential countries because of country rich cultural and geographical diversity. These trends also bring uncertainty about the flight ticket price. It can be hard to guess the flight ticket price when we check it today compared to the other day. The tourists who want to visit a new place in India should know the ticket price in order to get the cheapest and certain ticket price with their needs. This gap brings the idea to make a prediction about the flight tickets in order to make the tourists easier to book their tickets with their needs.

Technology can bring a solution through the implementation of Machine learning techniques to improve the uncertainty of flight prices in the future. We will use Flight Price Dataset provided by Kaggle Flight Price. This dataset consists of 10683 records with 13 columns that explain about the flight in India by some Indian and foreign Airlines in 2019. We will analyze this dataset using Machine learning techniques in order to predict the flight ticket price based on the features provided in the columns of the dataset. We will begin the Data Science Life Cycle to process the data.

#kaggle #data-science #pandas-dataframe #machine-learning