AI & Deep Learning
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Date: March 3, 2021
Time: 11:00am – 12:00pm PT
Duration: 1 hour

NVIDIA pre-trained deep learning models and the Transfer Learning Toolkit (TLT) give you a rapid path to building your next AI project. Whether you’re a DIY enthusiast or building a next-gen product with AI, you can use these models out of the box or fine-tune with your own dataset. The purpose-built, pre-trained models are trained on the large datasets collected and curated by NVIDIA and can be applied to a wide range of use cases. TLT is a simple AI toolkit, shipped with Jupyter notebooks, that requires little to no coding for taking pre-trained models and customizing them with your own data.

In this webinar, we’ll show you how to train your own gesture recognition deep learning pipeline. We’ll start with a pre-trained detection model, repurpose it for hand detection, and use it together with the purpose-built gesture recognition model. Once trained, we’ll deploy this model on NVIDIA® Jetson™. The gesture-recognition application can be deployed on a robot to understand human gestures and interact with humans. In addition, TLT supports other pre-trained models such as facial landmark estimation, gaze estimation, people detection, and many more. Using pre-trained models and TLT lets you accelerate your development time—from concept to production.

Join this webinar to explore:
  • Highly optimized pre-trained models for various industry use cases
  • How to fine-tune with your own data on new pre-trained models and use them to reduce your total development time
  • Developing an end-to-end training pipeline and deploying the trained model on NVIDIA SDKs

You can also find the github repo for the sample code used in this webinar.



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

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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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Ekaterina Sirazitdinova

Data Scientist at NVIDIA

Ekaterina Sirazitdinova is a data scientist at NVIDIA specialized in solving computer vision and video analytics problems using AI. Her focus also includes fast deep learning inference on embedded devices.

Nyla Worker

Solutions Architect at NVIDIA

Nyla Worker is a solutions architect at NVIDIA focused on simulation and deep learning within embedded devices. She has extensive experience working on deep learning edge applications for robotics and autonomous vehicles, as well as developing accelerated inference pipelines for embedded devices.

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Webinar: Description here

Date & Time: Wednesday, April 22, 2018