This is a machine learning project by Zining Wang, Jiayu Yao and Qiyang Li.
The goal is to recommend users with their favorite movies. We applied different models on movie rating dataset, and compare the results. Popular methods such as using averages, SVD with stochastic gradient descent were used here as baseline models. The innovative part is to use different demographic information and using our modified version of k nearest neighbors, XGBoost, and some ensemble learnings.
This repository is mainly used as study purpose for people who want to learn recommendation system. Thanks Vicky Wu for testing the study material.
- baseline models are in Baseline.ipynb
- common approach SVD with stochastic gradient descent is in SVD+bias.ipynb
- knn and further models are in knn.ipynb
- sim.ipynb is mainly used for test purpose and studying different distance metrics.