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39 changes: 39 additions & 0 deletions Projects/3-Advanced/Recommendation_System.md
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# Recommendation System

**Tier:** 3-Advanced

A recommendation system is an essential tool in today's digital world, allowing users to discover items based on their preferences and history. This project aims to create a recommendation system that provides personalized suggestions based on user behaviors.

### Constraints

- Recommendations should not be based solely on random criteria; they must be calculated using machine learning algorithms.
- The system must handle real data and meet performance constraints.

## User Stories

- [ ] User can create an account and log in to save their preferences.
- [ ] User can see a homepage with personalized recommendations based on their history.
- [ ] User can view details of a recommended item, including a description, rating, and similar items.
- [ ] User can rate items and update their preferences, thereby influencing future recommendations.
- [ ] User can navigate through a list of recommended items sorted by relevance.
- [ ] User can delete their account and all associated data.

## Bonus Features

- [ ] User can receive recommendations based on items similar to those they have already viewed.
- [ ] User can share their recommendations on social media.
- [ ] User can view the history of their recommendations and interactions with the system.

## Useful Links and Resources

- [Introduction to Recommendation Systems](https://towardsdatascience.com/introduction-to-recommendation-systems-in-python-308b3e3e6c6e)
- [Collaborative Filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)
- [Content-Based Filtering](https://en.wikipedia.org/wiki/Content-based_filtering)

## Example Projects

- [MovieLens Recommendation System](https://grouplens.org/datasets/movielens/)
- [Surprise: A Python library for building and analyzing recommender systems](https://github.com/NicolasHug/Surprise)
- [Netflix Prize Recommendation System](https://github.com/Netflix/Netflix-Prize)
- [RecSys Challenge](https://recsys.acm.org/recsys16/challenge.html)