Deep Learning for Clothing Review Analysis: Multi-Label Classification of Business Aspects"

This project leverages deep learning to classify user reviews into key clothing business aspect categories such as durability and finishing using BERT. By automating the analysis of customer feedback, businesses can efficiently identify user concerns, improve product quality, and enhance recommendation systems. The model processes large volumes of reviews in real-time, transforming unstructured feedback into actionable insights for targeted quality control and inventory management. Built with PyTorch and Hugging Face Transformers, it employs a multi-label classification approach and evaluates performance using F1-score, precision, and recall. This project provides a scalable solution for businesses to make data-driven, customer-centric decisions in the fashion industry.