In the bustling world of restaurants and bars, understanding customer behavior is crucial. One particular challenge faced by waitstaff is predicting tips accurately. This project aims to solve that problem with a machine learning approach.
📊 Project Overview
This Python program predicts how much a waiter might earn in tips on a particular day based on various factors like table size, bill amount, time of day, and other service variables. Predicting tips aids in service optimization, leading to satisfied customers and a thriving business.
🛠️ Technologies Used
- Python
- pandas for data processing
- scikit-learn for machine learning algorithms
- CSV data processing
🧠 How It Works
The model analyzes historical tipping data to identify patterns and correlations between various factors and tip amounts. By feeding new data into the trained model, it can predict potential tip earnings with reasonable accuracy.
🔍 Key Features
- Data preprocessing and cleaning
- Feature selection and engineering
- Model training and evaluation
- Prediction interface for new data inputs
Explore the source code on GitHub: predict-Waiter-Tip