Movie recommender system

This repository contains a Movie Recommender System built using machine learning algorithms to suggest personalized movie recommendations based on user preferences. The recommender system utilizes content based filtering to generate movie suggestions based on either user behavior or movie attributes.

Features

• Movie Recommendations: Get top 5 movie recommendations based on a selected movie.
• Movie Posters: Display movie posters fetched from the TMDB API.
• Interactive UI: Built with Streamlit for a smooth and responsive user experience.
• Cloud Hosting: Deployed on platforms like Streamlit Community Cloud or Render.

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Installation

1. Clone the repository:

git clone https://github.com/ishitab02/movie-recommender-system.git

2. Navigate to the project directory:

cd movie-recommender-system

3. Install the required dependencies:

pip install -r requirements.txt

Usage

To run the movie recommendation system, execute the following command:

streamlit run app.py

Navigate to the provided URL to interact with the application.

Dependencies

The project relies on several Python packages listed in requirements.txt, including but not limited to:

• Streamlit for creating the web app
• Pandas for data manipulation
• Numpy for numerical operations
• Requests for API calls
• Scikit-learn for machine learning tasks
• NLTK (Natural Language Toolkit) for natural language processing tasks
• Pickle for serialization and deserialization of Python objects