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Date: Wednesday, June 22, 2022
Time: 10:00am - 11:00am PT
Duration: 1 hour

Organizations across industries are leveraging computer vision (CV) to gather insights, improve the customer experience, and drive operational efficiencies. However, building a CV application requires large amounts of labeled data, software and hardware infrastructure to train the AI models, and tools to run real-time inference that will scale with demand. 

Join this webinar to find out how performance-optimized AI software and pre-trained models, available from the NVIDIA NGC™ catalog, help companies quickly build AI-powered applications with a fraction of the training data.

You’ll see how to deploy the software and the models from the NGC catalog through Jupyter Notebooks with a single click on Google Cloud Vertex AI, build an action recognition application service using various artifacts from the NGC catalog, and use this example as a template for building your own CV applications.

By attending this webinar, you will learn:
  • How to deploy Jupyter Notebooks for AI software and ML models from the NGC catalog on Google Cloud Vertex AI
  • How Google Cloud's Vertex AI Workbench helps users build ML models faster through access to data and analytics services, on-demand GPUs, distributed spark clusters, and pre-built runtimes for major frameworks
  • How various CV models, including action recognition and object detection, help accelerate development
  • How to customize models for your use case with NVIDIA TAO and run inference with DeepStream on scalable systems
Join us after the presentation for a live Q&A session.



You will receive an email with instructions on how to join the webinar shortly.


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DGX Station Datasheet

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DGX Station Whitepaper

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Chintan Patel

Senior Product Marketing Manager, NGC, NVIDIA

Chintan Patel is focused on bringing GPU-accelerated solutions to the high performance computing (HPC) community. He leads the management and offering of HPC application containers in the NGC catalog. Prior to NVIDIA, he held product management, marketing, and engineering positions at Micrel, Inc. He holds an MBA from Santa Clara University and a bachelor's degree in electrical engineering and computer science from UC Berkeley.

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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Webinar: Description here

Date & Time: Wednesday, April 22, 2018