A machine learning project that predicts suitable dyes for different fabrics using real-world data and Python pandas.
This project analyzes fabric properties and historical dyeing data to predict optimal dyes for various textile materials. The system helps in selecting the most effective dye compounds based on fabric characteristics, dye properties, and historical success rates.
- Data Analysis: Comprehensive analysis of fabric-dye relationships
- Prediction Model: Machine learning model for dye recommendation
- Real Data: Based on actual textile industry data
- Pandas Integration: Efficient data manipulation and processing
- Fabric Classification: Supports multiple fabric types (cotton, silk, polyester, etc.)
- Dye Optimization: Recommends dyes based on color fastness, cost, and effectiveness