This repository contains a Jupyter notebook that demonstrates the creation of a content-based movie recommendation system using Natural Language Processing (NLP) in Python.
This project is based on Emma Grimaldi’s tutorial on building a content-based movie recommender system. The system suggests movies based on user interests by analyzing movie descriptions and finding similar content.
Recommends movies similar to those the user likes.
Utilizes Python’s NLP libraries to process and analyze movie descriptions.
Provides a step-by-step guide and code implementation.
-
Clone the repository:
git clone https://github.com/cizodevahm/Recommendation-System-On-IMDB.git
-
Navigate to the project directory:
cd cizodevahm/Recommendation-System-On-IMDB
-
Install the required dependencies:
pip install pandas rake-nltk numpy scikit-learn
- Open the Jupyter notebook:
jupyter notebook NLP_Recommendation_System.ipynb
- Follow the instructions in the notebook to run the code cells and build the recommendation system.
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the GPL-3.0 license.