Our objective is to build a production-quality movie recommendation pipeline which provides a personalizied 5 top list of movies specific to each users. The goal of this new pipeline is to increase user retention for the platform and provide a better experience.
We will be using adataset from the GroupLens research lab at the University of Minnesota
The dataset is compressed into ml-latest.tar.gz.
To extract the data set, run:
tar -xvzf ml-latest.tar.gz- Clone the repository:
git clone https://github.com/your-username/your-repo.git
2.Navigate to the project Directory
cd your-repo3.Install the required dependencies
pip install -r requirements.txt1.Preprocess the data
python src/data_processing.py2.Train the reccommendation Model
python src/model_training.py3.Generate Movie Recommendation for user
python src/recommender.py --user_id Install the python packages enlisted in the requirements.txt
To install them run:
pip install -r requirements.txtIf you`d like to contribute please follow the following steps:
- Fork the repository
- Create a new branch
- Commit your changes
- Submit a pull request
For questions or feedback.kindly reach out:
- Email:mulwajose.jm@gmail.com
- Github:Github