This project analyzes the interactions that users have with articles on the IBM Watson Studio platform, and the goal of this project is to create a recommendation system that shows the articles that are most relevant to a specific user.
- pandas
- numpy
- matplotlib
- pickle
The repository contains a Jupyter notebook with the analysis and a copy of it in html format along with test scripts used in the notebook. The tasks involved are Exploratory Data Analysis, Rank Based Recommendations, User-Based Colloborative Filtering and SVD-Matrix Factorization.
Thank you IBM and Udacity for providing an opportunity to work on this project!