Linear regression analysis to uncover insights into customer behaviors and trends, leveraging machine learning for practical business applications. This repository presents a comprehensive project on Customer Behavior Analysis using Linear Regression, a key machine learning technique. The project is encapsulated in a Jupyter notebook which walks through the entire process of analyzing customer data. Key steps include data preprocessing, feature selection, implementing linear regression models, and interpreting the results to understand customer behaviors and trends.
The project aims to provide valuable insights into how customer attributes influence certain outcomes or behaviors, such as purchase patterns, product preferences, or customer lifetime value. Emphasis is placed on the practical application of linear regression in a real-world business context, demonstrating how data-driven insights can inform business strategy and decision-making.
Visualizations and statistical analyses within the notebook aid in making the data more comprehensible and in highlighting significant patterns and correlations. This project serves as an excellent resource for those looking to understand the fundamentals of machine learning in the context of customer data analysis.