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Movie Recommendation Website

Overview

This website utilizes machine learning models to recommend the top 5 movies based on user input. The recommendation system is implemented using Streamlit for the web interface and Jupyter Notebook for building and training the machine learning models.

Features

  • Recommends the top 5 movies similar to the user-provided movie.
  • Utilizes machine learning models trained on a dataset of movie features.
  • The web interface is created using Streamlit, providing an interactive user experience.

Technologies Used

  • Streamlit
  • Jupyter Notebook
  • Machine Learning Models
  • Python
  • Git

How it Works

  1. User Input: Users select a movie from the dropdown menu on the website.

  2. Recommendation System:

    • The selected movie is used as input to the machine learning models.
    • Similarity scores are calculated to find the most similar movies.
    • The top 5 recommended movies are displayed on the website.
  3. Web Interface:

    • The website is created using Streamlit for a user-friendly experience.
    • Users can easily interact with the recommendation system.

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