##Overview This prototype shows how to build recommender systems using Python libraries.
##Usage
Open recommender-systems folder with jupyter notebook
##Dependencies
- numpy
- pandas
- scikit-learn
- scipy
Use pip to install dependencies.
##Recommend systems
- Load music data
- The most popular movies in the dataset
- Popularity based recommender class
- A recommender with personalization
- User based (user-item) collaborative filtering
- Item based (item-item) collaborative filtering
- Quantitative comparison between the models
- Precision - How much junk did we give to user?
- Recall - How much of the good stuff did we miss?
##Credits
- The movie recommender systems are based on dvysardana.
- The dataset is from movielnes