Welcome to the "Travel Package Purchase Prediction" project. This analysis is a part of the "Ensemble Techniques" course and involves a detailed study of customer data provided by the "Visit with us" travel company. The primary aim is to build an ensemble model that can predict which customers are likely to purchase a newly introduced travel package.
This project entails the application of ensemble learning methods to create a robust predictive model. By analyzing customer data, we strive to understand the driving factors behind travel package purchases and predict customer behavior regarding a new offer.
- Data Exploration: Scrutinize the dataset to understand the demographics, purchasing history, and behavior of the travel company's customers.
- Predictive Modeling: Implement ensemble techniques to build a model that predicts the likelihood of a customer purchasing the new travel package.
- Insight and Analysis: Draw actionable insights for targeted marketing strategies, helping to drive sales of the new package.
- Familiarity with ensemble learning methods.
- Required software: Python, along with libraries like numpy, pandas, scikit-learn, matplotlib, and seaborn.