For this project I analyze the interactions that users have with articles on the IBM Watson Studio platform, and make recommendations to them about new articles they will like.
- Exploratory Data Analysis
- Rank Based Recommendations
- User-User Based Collaborative Filtering
- Matrix Factorization
Numpy, Pandas, Seaborn, Pickle
The code is in Jupyter notebook and .html file format with several notes and instructions for use in future projects. There are also files linked to the document like data, test, and pickles files.
This app was completed as part of the Udacity Data Science Nanodegree Program. Code templates and data were provided by Udacity.