Building a Simple Recommender System Using Popularity - Non-Personalized Approach

Explore the process of building a basic recommender system using popularity-based methods with the MovieLens dataset. Learn how to implement non-personalized recommendation techniques, including number of votes, mean rating, and damped mean. Discover why these methods serve as strong baselines in the field of recommender systems. Follow along as the video demonstrates data analysis, implementation of different popularity metrics, result comparison, and code optimization. Gain practical insights into creating a foundation for more advanced recommender systems.

- Introduction
- MovieLens dataset
- Number of votes
- Mean rating
- Damped Mean
- Comparing results
- Cleaning up code
- Ending