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Introduction

Date: February 18, 2021
Time: 11:00am – 12:00pm PT
Duration: 1 hour


Recommender systems predict user preferences for products based on historical behavior and are widespread in online retail, social media, streaming video and music platforms, and more.


However, building, training, and optimizing a recommender system model can be quite time consuming for novices and experts alike. To achieve a state-of-the-art model, you need to set up the right environment, train with the correct hyperparameters, and optimize it to achieve the desired accuracy. In this webinar, you’ll explore the NVIDIA® NGC™ catalog—which has a whole host of GPU-optimized AI software such as containers, pre-trained models, and use case-based Jupyter notebooks—and how to use these resources to kickstart your AI journey.



In this webinar you will learn:
  • About the NGC catalog and how it helps accelerate your AI workflows
  • How to leverage a Jupyter notebook containing a pre-trained recommender system model that can be used to recommend a movie based on a user’s viewing history
  • How to refine the model by retraining it using your own hyperparameters and test it using your own checkpoints
Join us after the presentation for a live Q&A session.

Click here to register for the session on Image Segmentation at 9am PT

WEBINAR REGISTRATION

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DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.

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Speakers

Akhil Docca

Senior Product Marketing Manager, NGC, NVIDIA

Akhil Docca is a senior product marketing manager for NGC at NVIDIA, focusing in HPC and DL containers. Akhil has a Master’s in Business Administration from UCLA Anderson School of Business and a Bachelor’s degree in Mechanical Engineering from San Jose State University.

Shokoufeh Monjezi Kouchak

Technical Marketing Engineer, NVIDIA

Shokoufeh is a technical marketing engineer at NVIDIA, focusing on deep learning models. Shokoufeh obtained her Phd degree in computer engineering from Arizona State University, where she focused on driver behavior analysis and driver distraction detection with deep learning models.

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Register

Webinar: Description here

Date & Time: Wednesday, April 22, 2018