Recommendation-System-On-IMDB

This repository contains a Jupyter notebook that demonstrates the creation of a content-based movie recommendation system using Natural Language Processing (NLP) in Python.

Overview

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.

Features

Content-Based Filtering:

Recommends movies similar to those the user likes.

NLP Techniques:

Utilizes Python’s NLP libraries to process and analyze movie descriptions.

Interactive Jupyter Notebook:

Provides a step-by-step guide and code implementation.

Installation

1. Clone the repository:

   git clone https://github.com/cizodevahm/Recommendation-System-On-IMDB.git

2. Navigate to the project directory:

   cd cizodevahm/Recommendation-System-On-IMDB

3. Install the required dependencies:

   pip install pandas rake-nltk numpy scikit-learn

Usage

1. Open the Jupyter notebook:

   jupyter notebook NLP_Recommendation_System.ipynb

2. Follow the instructions in the notebook to run the code cells and build the recommendation system.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the GPL-3.0 license.