Build next generation recommenders with NVIDIA Merlin | AISC

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Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=HQ1lBKp0qvc


Duration: 1:01:48
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26

Speaker(s): Even Oldridge
Facilitator(s): Omar Nada

Find the recording, slides, and more info at https://ai.science/e/build-next-generation-recommenders-with-nvidia-melrin--nHExEwn5NOrb6FQcand4

Motivation / Abstract
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.

What was discussed?
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.


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