This project aims to build a recommender system for articles on IBM Watson Studio platform to users. Different methods will be applied depending on the data, including: Knowledge-based recommendation, Collaborative recommendation and Single Value Decomposition method to find latent factors
Run pip install requirements.txt to install necesary packages
The project includes
- a data folder with two csv files used in the notebook
- Recommendations_with_IBM.ipynb: a Jupyter notebook with all the analysis and implementation of the recommender system
- Other supporting files for testing the outputs in the notebook
The dataset on articles and users interaction is from IBM Watson Studio and this project is a part of Udacity Data Science Nanodegree program