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End-to-End-Movie-Recommendation-System-with-deployment-using-docker-and-kubernetes

Content Based Recommendation system uses attributes of the content to recommend similar content. It doesn't have a cold-start problem because it works through attributes or tags of the content, such as actors, genres or directors, so that new movies can be recommended right away.

  • Updated May 2, 2022
  • Python

This project creates a dynamic pricing system that uses real-time data and machine learning to adjust taxi fares in real-time, responding to shifting market conditions. Additionally, it offers users personalized ride booking recommendations to boost satisfaction. Continuous learning capabilities ensure the system adapts and improves over time.

  • Updated Oct 15, 2024
  • Jupyter Notebook

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