How does Scala support scalable recommendation systems?

Scala supports recommendation systems using distributed computation and streaming feature pipelines.

Recommendation systems in Scala are built using Spark MLlib for batch training and streaming pipelines for real-time updates. Collaborative filtering, matrix factorization, and embedding models are trained on distributed clusters. Feature stores maintain consistent data across training and inference pipelines.