Wine Classification with Multi-layer Perceptron (MLP)

Project Overview

This project involves the development of a Multi-layer Perceptron (MLP) model from scratch to classify wines into three types based on chemical analysis attributes. The model implements backpropagation and utilizes 5-fold cross-validation to evaluate performance. The baseline model outputs random predictions for comparison.

Key Outcomes

• Implemented MLP with backpropagation from scratch.
• Achieved high accuracy compared to the baseline model.
• Evaluated model performance using 5-fold cross-validation.

Tools Used

• Python
• NumPy
• Pandas
• Jupyter Notebook

View the Code

Click the link below to view the full code and documentation for this project on GitHub:

View on GitHub