From Gradient-Boosted Trees to Deep Recommenders: Practical Lessons from Migrating a Production Customer Support Recommender

Sonia Sharma, Jeyendran Balakrishnan, Shreya Rajpal, Swapnil Parekh, Nagaraj Janardhana, and Andrew Mattarella-Micke.

We share practical lessons from migrating a live customer-support recommendation system from a gradient-boosted multiclass model to a pairwise-binary deep recommender. The deep approach matches the CatBoost baseline early in conversations and outperforms it at later stages.