Karl Higley

This repository contains the POPROX recommender code — the end-to-end logic for producing recommendations using article data, user histories and profiles, and trained models.

Core Utilities for NVIDIA Merlin

Merlin Systems provides tools for combining recommendation models with other elements of production recommender systems (like feature stores, nearest neighbor search, and exploration strategies) into end-to-end recommendation pipelines that can be served with Triton Inference Server.

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.