A recommender system is a subclass of information filtering system that seeks to predict the “rating” or “preference” a user would give to an item. Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and products in general.
- Collaborative filtering
- Content-based filtering
- Hybrid
Here i will use some interesting technics with explanation in notebook.
- Data needed to build a recommender
- Libraries available in Python to build recommenders
- Use cases
Used movies 100k dataset is a stable benchmark dataset with 100,000 ratings given by 944 users for 1664 movies, with each user having rated at least 20 movies.
Setting up the environment: python==3+
Libraries used:
- scikit-surprise
- pandas
- numpy
- scipy
- matplotlib
surprise library overview: https://www.youtube.com/watch?v=z0dx-YckFko&t=297s