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This project aims to build a game recommendation system for Steam users using machine learning techniques. It utilizes a custom dataset of Steam IDs to retrieve user-specific information such as owned games, playtimes, and game tags through the Steam Web API. The collected data is then processed and used to train a machine learning model.
A distributed system that provides a service to store, retrieve, and analyse the game data of popular multiplayer online survival games such as CS: GO, PUBG, Fortnite, etc.