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recommendersystem

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An age and context sensitive movie recommendation system for a group of people spanning various age groups that considers the preferences, past activities, and currently trending content to recommend an age-appropriate movie for all to enjoy

  • Updated Dec 4, 2022
  • Jupyter Notebook

This project develops a hotel recommendation system using content-based filtering. By analyzing hotel features such as room types, amenities, and pricing, it provides personalized suggestions for users. The model uses techniques like TF-IDF and evaluates its performance based on Precision@5, achieving high accuracy in recommendations.

  • Updated Feb 17, 2025
  • Jupyter Notebook

Music recommendation system that leverages the power of machine learning to provide personalized music suggestions based on user preferences. Using a hybrid approach combining K-Means Clustering and Cosine Similarity.

  • Updated Jan 29, 2025
  • Jupyter Notebook

Zee Recommender Systems is a personalized movie recommendation project built using the MovieLens dataset. It implements collaborative filtering, similarity-based models, and matrix factorization to enhance user experience by suggesting movies tailored to individual preferences. Includes EDA, evaluation (RMSE & MAPE) and visualization of embeddings.

  • Updated Dec 26, 2025
  • Jupyter Notebook

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