Online Retail Product Recommendation Samples

This is a code sample repository for online retail product recommendations using Collaborative Filtering (Memory-Based, aka History-Based). The source data used the famous Online Retail Data Set from UCI Machine Learning Repository.

• /data/Online Retail.xlsx <-- Online Retail Data Set from UCI Machine Learning Repository
• item_to_item_by_collaborative_filtering.ipynb <-- Product-Based Filtering, Product-to-Product product recommendations.
• user_to_user_by_collaborative_filtering.ipynb <-- User-Based Filtering, User-to-User product recommendations.

Below is a list of categories of Recommendation Systems to achieve different objectives.

• Collaborative Filtering
  • Memory Based (aka History Based)
    • Product-Based Filtering
    • User-Based Filtering
  • Model Based (e.g., Alternating Least Square (ALS))
  • Hybrid
• Content-Based Filtering
• Hybrid

Enjoy!