Offline to Online: Feature Storage for Real-time Recommendation Systems with NVIDIA Merlin
Recommendation models have progressed rapidly in recent years due to advances in deep learning and the use of vector embeddings. The growing complexity of these...
Upcoming Event: Recommender Systems Sessions at GTC 2022
Learn about transformer-powered personalized online advertising, cross-framework model evaluation, the NVIDIA Merlin ecosystem, and more with these featured GTC...
Scaling Recommendation System Inference with NVIDIA Merlin Hierarchical Parameter Server
Recommendation systems are widely used today to personalize user experiences and improve customer engagement in various settings like e-commerce, social media,...
Join us to hear featured speakers from Netflix, Twitter, Weights & Biases, Coveo, and more discuss challenges building, training, optimizing, and deploying...
Accelerating Embedding with the HugeCTR TensorFlow Embedding Plugin
Recommender systems are the economic engine of the Internet. It is hard to imagine any other type of applications with more direct impact in our daily digital...
Accelerating Recommender Systems Training with NVIDIA Merlin Open Beta
NVIDIA Merlin is an open beta application framework and ecosystem that enables the end-to-end development of recommender systems, from data preprocessing to...
Introducing NVIDIA Merlin HugeCTR: A Training Framework Dedicated to Recommender Systems
Click-through rate (CTR) estimation is one of the most critical components of modern recommender systems. As the volume of data and its complexity grow rapidly,...
Accelerating ETL for Recommender Systems on NVIDIA GPUs with NVTabular
Recommender systems are ubiquitous in online platforms, helping users navigate through an exponentially growing number of goods and services. These models are...
Announcing NVIDIA Merlin: An Application Framework for Deep Recommender Systems
Recommender systems drive every action that you take online, from the selection of this web page that you’re reading now to more obvious examples like online...
