https://github.com/simplecyber/movie-recommendation-system

Movie Recommendation System : built using Streamlit, Pandas, and the TMDb API. It allows users to select a movie and get five similar movie recommendations along with their posters.
https://github.com/simplecyber/movie-recommendation-system

python streamlit tmdb-api

Last synced: about 1 month ago
JSON representation

Movie Recommendation System : built using Streamlit, Pandas, and the TMDb API. It allows users to select a movie and get five similar movie recommendations along with their posters.

• Host: GitHub
• URL: https://github.com/simplecyber/movie-recommendation-system
• Owner: SimpleCyber
• Created: 2024-12-21T14:08:05.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2024-12-21T14:22:04.000Z (about 1 month ago)
• Last Synced: 2024-12-21T15:22:21.821Z (about 1 month ago)
• Topics: python, streamlit, tmdb-api
• Language: Jupyter Notebook
• Homepage:
• Size: 1.28 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Movie Recommendation System 🎥

This is a **Movie Recommendation System** built using **Streamlit**, **Pandas**, and the **TMDb API**. It allows users to select a movie and get five similar movie recommendations along with their posters.

## Features

- **Movie Recommendations**: Get top 5 movies similar to the one you select.

- **Poster Display**: View the posters of the recommended movies.

- **Interactive Interface**: Built with an easy-to-use Streamlit interface.

## Installation

1. Clone the repository:

   ```bash

   git clone https://github.com/SimpleCyber/Movie-Recommendation-system.git

   ```

2. Navigate to the project directory:

   ```bash

   cd Movie-Recommendation-system

   ```

3. Install the required dependencies:

   ```bash

   pip install -r requirements.txt

   ```

4. Download the necessary `.pkl` files (`movies_dict.pkl` and `similarity.pkl`) and place them in the root directory.

## Usage

1. Run the Streamlit app:

   ```bash

   streamlit run app.py

   ```

2. Open your browser and go to the URL displayed in the terminal (default: `http://localhost:8501`).

3. Select a movie from the dropdown and click "Recommend" to view recommendations.