Best Practices for Building and Deploying Recommender Systems
This document describes the best practices for building and deploying large-scale recommender systems using NVIDIA GPUs. These practices are the culmination of years of research and development in GPU-accelerated tools for recommender systems, as well as building recommender systems for our in-house products and top-performing solutions for international recommendation systems competitions.
Recommender systems are the economic engine of the Internet. These applications have a direct impact on our daily digital lives in which they filter products and services among an overwhelming number of options, easing the paradox of choice that most users face.
The primary goal of this document is to provide best practices for building and deploying large-scale recommender systems using NVIDIA® GPUs. These best practices are the culmination of years of research and development in GPU-accelerated tools for recommender systems, as well as building recommender systems for our in-house products and top-performing solutions for international recommendation systems competitions.
This document doesn’t only provide best practices for building and deploying large-scale recommender systems, but it also covers all facets of recommender systems with a focus on GPU acceleration and optimization.
