NVIDIA Merlin™ is an open-source framework for building large-scale deep learning recommender systems.
Designed for Recommender Workflows
Merlin empowers data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes libraries, methods, and tools that democratize building deep learning recommenders by addressing common preprocessing, feature engineering, training, and inference challenges. Each component of the Merlin pipeline is optimized to support hundreds of terabytes of data, all accessible through easy-to-use APIs. With Merlin, better predictions than traditional methods and increased click-through rates are within reach.
An End-to-End Referential Architecture
NVIDIA Merlin accelerates the entire pipeline, from ingesting and training to deploying GPU-accelerated recommender systems. Merlin's open-source components simplify building and deploying a production-quality pipeline.
Merlin NVTabular is a feature engineering and preprocessing library designed to effectively manipulate terabytes of recommender system datasets and significantly reduce data preparation time.
Merlin HugeCTR is a deep neural network training framework designed for recommender systems. It provides distributed training with model-parallel embedding tables and data-parallel neural networks across multiple GPUs and nodes for maximum performance.
Accelerate Recommenders on NVIDIA GPUs
Learn about the recommender system training pipeline, the technical advantages of NVTabular, benchmarking results, and how to get started.
Merlin Technical Resource Kit
Learn how to accelerate the entire pipeline, from ingesting and training to deploying GPU-accelerated recommender systems.
NVIDIA Deep Learning Institute (DLI)
Register for this DLI workshop to learn the fundamental tools and techniques for building highly effective recommender systems.
Take this survey to share some information about your recommender pipeline and influence the NVIDIA Merlin roadmap.