How does TikTok's recommendation algorithm work and can we replicate it in a simple Python project?

15 Eyl 20:45

I've been diving into how short‑form platforms keep users hooked, and TikTok's recommendation engine keeps popping up in articles. I'm curious about the core concepts: what signals does it consider, how does it balance fresh content vs. personal taste, and which machine‑learning techniques are most common (e.g., collaborative filtering, deep learning, reinforcement loops). I'd love to build a tiny prototype in Python to experiment with similar ideas. Does anyone have beginner‑friendly explanations or open‑source resources we could explore together? Your thoughts would help a lot!