This project (Recommendations with IBM) is part of Udacity's Data Scientists Nanodegree Program.
This project builds a recommendation system, where it analyzes the interactions that users have with articles on the IBM Watson Studio platform, and make recommendations to them about new articles you think they will like. This project uses data from IBM Watson Studio platform.
Exploratory Data Analysis: Explores the data and provides statistics and visuals about the dataset.
Rank Based Recommendations: Provides recommendations based on Rank of top interacted aricles.
User-User Based Collaborative Filtering: Provides recommendations based on similarity between users and most articles interacted.
Matrix Factorization: Builds and evaluates a machine learning model based on user-item interaction and matrix decomposition.
This project is provided as Jupyter notebook, it's also available in HTML format.