# 🎬 Movie Recommendation System A full-stack web application that recommends movies to users based on their preferences using a Machine Learning model in Python and a modern frontend built with Next.js. --- ## 🧠 How the Recommendation Model Works The recommendation engine is built using **collaborative filtering** and/or **content-based filtering** techniques with libraries like `scikit-learn` or `Surprise`. --- ## ⚙️ Technologies Used | Layer | Technology | |-----------|----------------------| | Backend | Python, FastAPI| | ML Model | Scikit-learn, Surprise, Pandas | | Frontend | Next.js, TypeScript, Tailwind CSS | | Data | KuaiRand Dataset (or similar) | --- ## 🚀 Getting Started --- ### 1️⃣ Backend Setup (Python + FastAPI) ```bash # Navigate to the backend folder (if separated) cd backend # Create virtual environment python -m venv venv # On Windows: venv\Scripts\activate # on macos source venv/bin/activate # Install dependencies pip install -r ../requirements.txt #If you don't have Jupyter pip install notebook #start the jupyter jupyter notebook # Run FastAPI server uvicorn app:app --reload cd frontend # Install dependencies npm install # Run Next.js dev server npm run dev