/Netflix_Movie_Recommendation

This project implements a collaborative filtering-based recommendation engine for movie suggestions, inspired by Netflix's recommendation system. The recommendation engine utilizes matrix factorization, specifically Singular Value Decomposition (SVD), to predict user preferences and generate personalized movie recommendations.

Primary LanguagePython

Movie Recommendation App

Welcome to the Movie Recommendation App project repository! 🎬

Project Overview

This project is a Movie Recommendation App that suggests movies to users based on collaborative filtering. It uses a Singular Value Decomposition (SVD) model trained on movie ratings to provide personalized movie recommendations.

Key Features

  • User Selection: Users can select their user ID from a dropdown menu to receive personalized movie recommendations.
  • Recommendation Generation: The app generates movie recommendations based on the user's selected ID using the SVD model.
  • Interactive Interface: Streamlit is used to create an interactive web interface for users to select their ID and view recommendations.
  • Visualization: The app displays the top recommended movies along with a heatmap visualization of their estimated scores.

How to Use

  1. Clone the Repository: Clone this repository to your local machine using https://github.com/Raghavendra0827/Netflix_Movie_Recommendation.git.
  2. Install Dependencies: Install the required dependencies listed in requirements.txt using pip install -r requirements.txt.
  3. Run the App: Execute the Streamlit web application by running streamlit run app.py in your terminal.
  4. Select User ID: Select a user ID from the dropdown menu to receive personalized recommendations.
  5. Get Recommendations: Click the "Recommend Movies" button to view the top recommended movies for the selected user.
  6. Explore Recommendations: Explore the recommended movies displayed in the app interface and discover new movies to watch!

About the Author

This Movie Recommendation App is developed by Raghavendra KN, a passionate developer dedicated to creating innovative solutions using Python and machine learning.

Get in Touch

Feel free to connect with the author for any inquiries or feedback:

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Acknowledgments

We extend our gratitude to the Python and Streamlit communities for their invaluable resources and support, enabling us to develop this Movie Recommendation App.