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Recommender System

A Recommender System (a.k.a. Collaborative Filtering, Social Filtering, and Social Information Filtering) is an information filtering technique that takes details and data associated with a user's profile and compares it with similar data (habits, likes, opinions, etc.) of other users on the same service in order to present recommendations of what might be of interest to the original user.

Examples of web services that make use of Recommender Systems are: online auction/ecommerce websites, music services, movie and television show streaming services, etc.

  • Frequently bought together for Retail
  • Top picks for you for Media and Entertainment

https://www.quora.com/LinkedIn-Recommendations/How-does-LinkedIns-recommendation-system-work

https://docs.aws.amazon.com/personalize/latest/dg/what-is-personalize.html

Vinija's Notes • Recommendation Systems • Research Papers

Social Media Recommendation Engine

  • Doom scrolling
  • Endless bottom / endless scrolling
  • Reel life vs real life

Price Recommendation Engine

ML driven dynamic pricing @ CARS24 - Part 1 | by Shashank Kumar | CARS24 Data Science Blog | Mar, 2023 | Medium