How to: Recommender Systems
_Libraries for building recommender systems._

- [annoy](https://github.com/spotify/annoy) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.
- [fastFM](https://github.com/ibayer/fastFM) - A library for Factorization Machines.
- [implicit](https://github.com/benfred/implicit) - A fast Python implementation of collaborative filtering for implicit datasets.
- [libffm](https://github.com/guestwalk/libffm) - A library for Field-aware Factorization Machine (FFM).
- [lightfm](https://github.com/lyst/lightfm) - A Python implementation of a number of popular recommendation algorithms.
- [spotlight](https://github.com/maciejkula/spotlight) - Deep recommender models using PyTorch.
- [Surprise](https://github.com/NicolasHug/Surprise) - A scikit for building and analyzing recommender systems.
- [tensorrec](https://github.com/jfkirk/tensorrec) - A Recommendation Engine Framework in TensorFlow.