Analyze user behavior and social network data on IBM Watson platform to build a recommendation engine based on to surface content most likely to be relevant to a user. This project consisted of building various types of recommendation engines such as rank-based, user-user collaborative filtering, and matrix factorization.
This project requires Python 3.x and the following Python libraries installed:
scikit-learn==0.21.2
pandas==0.24.2
numpy==1.16.4
matplotlib==3.1.0
You will also need to have software installed to run and execute an iPython Notebook
install Anaconda, a pre-packaged Python distribution that contains all of the necessary libraries and software for this project.
Analyze user behavior and social network data on IBM Watson platform to build a recommendation engine based on to surface content most likely to be relevant to a user. This project consisted of building various types of recommendation engines such as rank-based, user-user collaborative filtering, and matrix factorization.
Data:
The data is for IBM an online data science community