Hybrid Recommendation System (HRS)

#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: github.com/vir...
Project GitHub Repo: github.com/vir...
G-Mail: [e-mail]
Thank you for watching!