Detailed analysis of the interactions that users have with articles on IBM Watson Studio platform, along with a recommendation system to users about new articles.
There are 2 options available:
- Clone the repo:
git clone https://github.com/AhmadSherief/IBM-article-recommendation.git - Download the latest release
The objective of this project is to analyse the interactions that users have with articles on IBM Watson Studio platform, and build a recommendation system that recommend new articles to users.
The file is written in a Jupyter Notebook, and consists of the below secions:
- Exploratory Data Analysis.
- Rank Based Recommendations.
- User-User Based Collaborative Filtering.
- Matrix Factorization.
- Conclusion.
Code is released under the MIT License.