Recommendations with IBM Project

Build Recommendation Systems

Udacity Data Scientist Nanodegree Project

Project Motivation

This project builds up knowledged based, collaborative filtering based, and content based recommendation systems to recommend articles to users from the IBM Watson Studio platform.

Installation

1.Install Anaconda if you have not installed it. Otherwise, skip this step. 2.Update Anaconda by typing conda update -all in Anaconda Prompt. 3.Clone this repository to your local machine using:

$ git clone https://github.com/YueminLi/Recommendations_with_IBM.git

4.Run this Jupyter notebook in your local Anaconda Jupyter Notebook environment:

Recommendations_with_IBM.ipynb

File Descriptions

• data

  • articles_community.csv: csv file that contains information of articles posted on the IBM Watson Studio platform
  • user_item_interactions.csv: csv file that contains informatio of user and article interactions on the IBM Watson Studio platform
  • user_item_matrix.p: contains information of user_item_matrix

• recommendation systems

  • Recommendations_with_IBM.ipynb: Jupyter notebook that contains full codes to build up three recommendatio systems
  • Recommendations_with_IBM.html: html version of the Jupyter notebook

• test

  • project_tests.py: test file to check codes continuously
  • top_5.p: test file to check collaborative filtering recommender
  • top_10.p: test file to check collaborative filtering recommender
  • top_20.p: test file to check collaborative filtering recommender

• LICENSE

• README.md

Author

Yuemin Li

Github: https://github.com/YueminLi

LinkedIn: https://www.linkedin.com/in/yuemin-li-89166333/

License

Usage is provided under the MIT License. See LICENSE for the full details.