Online Product Recommender System
The methodology applied for this project.
Project Summary
- Built an online recommendation system to suggest customized items based on a 1M-observation like-unlike dataset.
- Applied Collaborative Filtering to calculate similarity scores among users using Pandas and achieved a 74% accuracy.