Recommendation Systems - A Deep Dive into Collaborative Filtering

Recommendation systems quietly power many of the decisions we see every day, from which movie Netflix suggests next to which product shows up at the top of your grocery app. In this video, we begin a new series with a deep, intuitive dive into collaborative filtering, the foundation behind many modern recommenders. You’ll learn how user-based and model-based approaches work, why “people similar to you also liked…” sometimes fails, and how matrix factorization uncovers hidden taste patterns that drive accurate recommendations at scale. This is a concept-first walkthrough designed to build real intuition before we jump into code in the next videos. RecSys 1