BigDL Friesian is an application framework for building optimized large-scale recommender solutions. The recommending workflows built on top of Friesian can seamlessly scale out to distributed big data clusters in the production environment.
Friesian provides end-to-end support for three typical stages in a modern recommendation system:
Offline stage: distributed feature engineering and model training.
Nearline stage: Feature and model updates.
Online stage: Recall and ranking.
Documents in these sections helps you getting started quickly with Friesian.
Key Features Guide
Each guide in this section provides you with in-depth information, concepts and knowledges about Friesian key features.
Use Cases and Examples.
API Document provides detailed description of Nano APIs.