Movie Recommendation System

This project showcases a Movie Recommendation System that uses collaborative filtering and content-based filtering techniques to suggest movies based on user preferences and viewing history.

Features

• Personalized recommendations: Suggests movies based on user ratings and preferences.
• Collaborative filtering: Analyzes user behavior and similarities to recommend movies.
• Content-based filtering: Recommends movies based on genre, director, cast, and keywords.
• Hybrid model: Combines collaborative and content-based filtering for improved accuracy.
• Real-time updates: Continuously learns from user interactions for better recommendations.

Installation

To set up the Movie Recommendation System on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/movie-recommender.git
   cd movie-recommender

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To use the Movie Recommendation System, start the application and enter your preferences or rate some movies to get personalized suggestions:

python app.py

Access the application in your web browser, and start exploring movie recommendations tailored to your taste.

Results

Experience personalized movie suggestions that match your viewing history, favorite genres, and more, offering an engaging and tailored movie-watching experience.