Building in-house recommendation engines – Celine Xu, Axel Johnson

Provide the insights about the important elements need to be considered for building an in-house recommendation system. How could maximize the usage of in-house reco engine. General introduction/summary about major methods/implementations of building recommendation system as well as the limitations/challenges of in-use algorithms.

Key Takeaways

  • Recommendation system is basically a scoring system blended with ML results and business rules, need to have a balanced approach for scoring.
  • Pre-set business targets, flexibility of code and continuously testing can maximize the usage of the engine.
  • Platform, Integration, and the change of way of work matter

Add comment