Repository Copy of: Churn Detection and User Classification via Machine Learning in the Food and Beverage Sector

Key Points

• The aim is to utilize machine learning techniques to identify customer churn and classify user segments in the food and beverage industry.
• Machine learning algorithms were employed for analyzing user data.
• A focus on churn prediction and user classification within the food and beverage sector was maintained.
• Data preprocessing and feature selection were integral to the analysis.
• Machine learning models effectively identified patterns in churn behavior.
• Classification accuracy improved through feature engineering techniques.
• Insights gained could aid in improving customer retention strategies.