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Movie Recommendation App

This project is a movie recommendation web application using Streamlit. Users can input their favorite movie, and the app provides recommendations based on movie similarities. Demo HERE

Getting Started

Prerequisites

  • Python 3.7 or higher
  • Pip (Python package installer)

Installation

  1. Clone the repository:

    git clone https://github.com/your-username/movie-recommendations.git
    cd movie-recommendations
  2. Install dependencies:

    pip install -r requirements.txt
  3. Run the Streamlit app:

    streamlit run app.py
  4. Open your browser and navigate to http://localhost:8501 to access the app.

Usage

  1. Select your favorite movie from the dropdown menu.
  2. Click the "Suggest Rabdom" button to view random movie recommendations.
  3. Recommendations will be displayed with movie names and posters.

Features

  • Recommends movies based on similarity scores.
  • User-friendly interface with dropdown and button interaction.

License

This project is licensed under the MIT License.

Acknowledgments

  • The dataset used in this project is sourced from Kaggle.

About

This project is a Streamlit-based web application that provides movie recommendations based on user input. It uses a collaborative filtering approach with count vectorization and cosine similarity to suggest movies similar to the user's favorites. The app allows users to input their preferred movies and receive personalized recommendations.

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