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#

personalized-recommendations

Here are 21 public repositories matching this topic...

EazyWed is a MERN-stack wedding planning platform that simplifies vendor booking, budget tracking, and digital invitations. With personalized recommendations and an AI-powered chatbot, it ensures an elegant and joyful wedding planning experience.

  • Updated Apr 25, 2025
  • JavaScript

A new package that helps software developers improve their learning strategies by analyzing their self-reported learning habits, goals, and challenges. It takes text input describing their current lea

  • Updated Dec 21, 2025
  • Python

LinkLens is a modular, GenAI-Powered Interest Discovery Framework that captures, analyzes, and leverages user behavior using a graph-based approach. Designed for scalability and deep personalization, LinkLens turns raw user interactions into meaningful, real-time recommendations by modeling behavior as relationships and patterns.

  • Updated May 11, 2025
  • Python

CinemAI is a sophisticated movie and TV show recommendation system that leverages cutting-edge AI technologies combined with traditional algorithms to provide personalized recommendations using AI embeddings, statistical clustering, and GPT-4 for intelligent movie suggestions.

  • Updated Jul 15, 2025
  • Python

Fantasy Home 🏡✨ Discover your dream home with Fantasy Home! Explore comprehensive property listings, utilize user-friendly search features, and experience interactive maps and virtual tours. Receive personalized recommendations and expert guidance to find the perfect place for you.

  • Updated Jun 1, 2025
  • JavaScript

🤖 Streamline bookings and payments with our AI-powered chatbot, designed for customers and teams using advanced multi-agent architecture.

  • Updated Feb 21, 2026
  • Python

Mobile courier management app. Real-time route tracking, ETA risk alerts, personalized route recommendations by using AI when delivery delays are likely, and proof-of-delivery confirmation. Optimized for individual couriers and small delivery teams.

  • Updated Feb 11, 2026
  • Dart

LaughterLens is a collaborative filtering-based recommendation system that predicts user preferences for jokes using cosine similarity. It provides personalized joke recommendations, evaluates performance with Mean Absolute Error, and compares results with a baseline random recommender system.

  • Updated Mar 24, 2025
  • Jupyter Notebook

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