# From-Scratch NumPy Content-Based Recommender: 150 Lines on MovieLens-100K

> Source: https://sukruyusufkaya.com/en/learn/oneri-sistemleri/sifirdan-numpy-content-based-recommender-movielens
> Updated: 2026-05-13T13:29:34.843Z
> Category: Öneri Sistemleri
> Module: Module 4: Content-Based Filtering
**TLDR:** The backbone lesson of this module: building a real content-based recommender on MovieLens-100K — pure NumPy, 150 lines, end-to-end. Item profiling, user profile vector, cosine scoring, top-N recommendation, evaluation. Then compare with sklearn and the first row in our baseline table.