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.
The recommendation engine is built using collaborative filtering and/or content-based filtering techniques with libraries like scikit-learn or Surprise.
| Layer | Technology |
|---|---|
| Backend | Python, FastAPI |
| ML Model | Scikit-learn, Surprise, Pandas |
| Frontend | Next.js, TypeScript, Tailwind CSS |
| Data | KuaiRand Dataset (or similar) |
# 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