Hybrid Recommendation System (HRS)

Опубликовано: 07 Август 2026
на канале: Coder VR
385
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#recommendationsystem #machinelearning #python #flask #reactjs #datascience #personalizedcontent #mongodb #googlecolab #tmdbapi #nodejs #expressjs #vscode #bootstrap5

Welcome to our Hybrid Recommendation System showcase! This video highlights our innovative approach to personalized content suggestions using content-based filtering, collaborative filtering, and knowledge-based techniques.

Key Features:
User Profiles: Collect and use demographic info and interactions.
Content-Based Filtering: Analyze genres, actors, and keywords.
Collaborative Filtering: Use ratings, reviews, and user history.
Dynamic Weighting: Improve recommendation accuracy.
Scalability: Efficient data processing and storage.

Technology Stack:
Frontend: Vite, React.js, Bootstrap.
Backend: Python Flask, Express, Node.js, MongoDB, TMDB API.
Data Analysis: Google Colab for training models and analysis.

Highlights:
Personalized recommendations based on user habits.
User-friendly interface for easy navigation.
Comprehensive evaluation for high user satisfaction.

Stay tuned to see our system in action. Like, comment, and subscribe for more updates!

Links:
GitHub: https://github.com/virajRaut25
Project GitHub Repo: https://github.com/virajRaut25/hybrid...
G-Mail: [email protected]

Thank you for watching!