Recommendation-System

In our project, we tried to implement a recommendation system using amazon beauty products data, we choose a smaller subset of amazon dataset. Dataset was downloaded from https://cseweb.ucsd.edu/~jmcauley/datasets/amazon_v2/, it's publically available for academic purposes. The datasets are in json format and there are two dataset, review_data and meta_data. Due to large file size i could not upload the file.

I have implemented 5 algorithms to build our Recommendation System based on Amazon Product Review (Beauty Product) Dataset. List of Algorithms:

1. Demographic Model with weighted function
2. Item Based Collaborative Filtering (KNNWithMeans)
3. Model Based Collaborative Filtering (SVD)
4. User Based Collaborative Filtering (SVD++)
5. User Based Collaborative Filtering (SVD) And used evaluation metric like recall, precision and RMSE.

I have used surprise from scikit-learn. Need to install it if not installed before. If you are using Anaconda Run Below Command

conda install -c conda-forge scikit-surprise