Prototyping a Live Product Recommender With Python
The article shows how to build a real-time product recommender prototype in Python using Contextual Multi-Armed Bandits to simulate user behavior and validate online learning algorithms like LinUCB. It explains why bandits handle cold-start and context better than traditional models, walks through data generation, feature engineering, offline evaluation, and sets up a live simulation as ...
https://jaehyeon.me/blog/2026-01-29-prototype-recommender-with-python/
The article shows how to build a real-time product recommender prototype in Python using Contextual Multi-Armed Bandits to simulate user behavior and validate online learning algorithms like LinUCB. It explains why bandits handle cold-start and context better than traditional models, walks through data generation, feature engineering, offline evaluation, and sets up a live simulation as ...
https://jaehyeon.me/blog/2026-01-29-prototype-recommender-with-python/
jaehyeon.me
Prototyping a Live Product Recommender with Python
Traditional recommenders struggle with cold-start users and short-term context. Contextual Multi-Armed Bandits (CMAB) continuously learns online, balancing exploitation and exploration based on real-time context. In Part 1, we build a Python prototype to…