implicit feedback

Architecture Digest

Aug 27, 2022 · Artificial Intelligence

Understanding Collaborative Filtering, Matrix Factorization, and Spark ALS for Recommendation Systems

This article explains the fundamentals of recommendation systems, introduces collaborative filtering (both user‑based and item‑based), derives the matrix‑factorization model with ALS optimization, provides a complete Python implementation, and demonstrates how to apply Spark ALS in both demo and production environments.

ALSRecommendation SystemSpark

0 likes · 29 min read

Understanding Collaborative Filtering, Matrix Factorization, and Spark ALS for Recommendation Systems

DataFunTalk

Jul 1, 2019 · Artificial Intelligence

Data-Driven Foundations for Building Recommendation Systems

The article explains how data serves as a critical asset for recommendation systems, outlining the necessary steps from understanding business problems and data dimensions to collection, cleaning, integration, and analysis, while distinguishing explicit and implicit user feedback and emphasizing data quality, timeliness, and relevance.

ETLdata collectiondata quality

0 likes · 11 min read

Data-Driven Foundations for Building Recommendation Systems