Recommender Systems are one of the most practical categories in Machine Learning, that is used to make millions of recommendations on a daily basis to users in a business.
NVIDIA Merlin is a framework for building high-performance, deep learning-based recommender systems.
Merlin includes tools for building deep learning-based recommendation systems that provide better predictions than traditional methods and increase click-through rates. Each stage of the pipeline is optimized to support hundreds of terabytes of data, all accessible through easy-to-use APIs. In this talk, we will go through the introduction to the following Merlin components and why they are key to your development of Deep Recommender Systems:
NVTabular reduces data preparation time by GPU-accelerating feature transformations and preprocessing.
HugeCTR is a deep neural network training framework that is capable of distributed training across multiple GPUs and nodes for maximum performance.
NVIDIA Triton™ Inference Server and NVIDIA® TensorRT™ accelerate production inference on GPUs for feature transforms and neural network execution.