Dropbox-Restaurants

Alongside five other students in the 2023-2024 cohort of MIT's Break Through Tech program, I used data from Kaggle to develop a recommendation system that uses users' past ratings of restaurants to suggest restaurants they haven't yet visited.

Files

• MatrixFactorization.ipynb: the Python code used to generate restaurant recommendations for users
• UsersRestaurantRatingsNew.csv: the dataset containing users' overall ratings, food ratings, and service ratings of restaurants
• UsersRestaurantRatingsMatrix.csv: the sparse matrix of user ratings with 138 rows (users) and 130 columns (restaurants)
• Maura Anish AI Studio Project Write-Up.pdf: the written summary of the project
• AI Studio Project Presentation.pdf: the presentation given on the Matrix Factorization and Content-Based Filtering methods used in the project