Movie-Recommender

This project implements a movie recommender system using TMDB movie data.

Dataset:

The movie data used for this project was downloaded from the TMDB Movie Metadata dataset on Kaggle.

Deployed Model:

This project also includes a deployed model on Hugging Face: Movie Recommender

Getting Started

This recommender system uses Python libraries. To run the application locally, you'll need to set up a virtual environment. Here are the instructions for creating a virtual environment:

Using pip:

1. Open your terminal or command prompt.
2. Install venv if you haven't already: python -m ensurepip install venv
3. Create a virtual environment named movie_rec_env: python -m venv movie_rec_env
4. Activate the virtual environment:
   • Windows: movie_rec_env\Scripts\activate
   • macOS/Linux: source movie_rec_env/bin/activate

Using conda:

1. Open your terminal or command prompt.
2. Create a virtual environment named movie_rec_env: conda create -n movie_rec_env python=3.x (Replace 3.x with your desired Python version)
3. Activate the virtual environment: conda activate movie_rec_env

Installing Dependencies:

1. Once your virtual environment is activated, navigate to the project directory in your terminal.
2. Install the required libraries listed in requirements.txt: pip install -r requirements.txt

Running the Application:

1. After installing the dependencies, run the application using: streamlit app.py

This will start the movie recommender system. You'll be able to interact with the application to receive movie recommendations based on your preferences.