This project is a movie recommendation system that provides users with personalized movie suggestions. It analyzes user preferences to recommend films they might enjoy.
- Personalized Recommendations: Offers suggestions based on user preferences.
- Data Analysis: Analyzes movie data to generate the best recommendations.
- Machine Learning: Continuously learns and improves through recommendation algorithms.
- Python: The main programming language for the project.
- Pandas: Used for data manipulation and analysis.
- NumPy: Utilized for numerical operations.
- Matplotlib: For data visualization.
- Seaborn: Provides a high-level interface for drawing attractive statistical graphics.
- AST: Used for safely evaluating string expressions.
- Warnings: To manage warning messages during execution.
- Scikit-learn: For machine learning model selection and evaluation (e.g.,
train_test_split). - TensorFlow: Used for building and training deep learning models.
- Clone this repository:
git clone https://github.com/Yigit033/movie-recommender.git