Retail Product Recommender Engine

Overview

A recommender engine is developed using 200,000 reviews at Rent the Runway to expose users to relevant products that tailor to their preferences.

Content-based recommenders and collaborative filtering systems are implemented, including K-Nearest Neighbors and Matrix Factorization algorithms.

The recommendations are generated according to predicted user ratings. Upon evaluation of the models, the Singular Value Decomposition resulted to the lowest mean absolute error of 0.5 on the five point rating scale.

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Github: Repository