Computer Vision / Video Analytics

On-Demand Technical Sessions: Develop and Deploy AI Solutions in the Cloud Using NVIDIA NGC

At GTC ’21, experts presented a variety of technical talks to help people new to AI, or just those looking for tools to speed-up their AI development using the various components of the NGC catalog, including:

  • AI containers optimized to speed up AI/ML training and inference
  • Pretrained models that provide an advanced starting point to build custom models
  • Industry-specific AI SDKs that transform applications into AI-powered ones
  • Helm charts to provide consistent and faster deployments
  • Collections that bring together all the software needed for various use cases

Watch these on-demand sessions to learn how to build solutions in the cloud with NVIDIA AI software from NGC.

Building a Text-to-Speech Service that Sounds Like You

This session shows how to build a TTS model for expressive speech using pretrained models. The model is fine-tuned with speech samples and customized for the variability in speech performing style transfer from other speakers. The provided tools let developers create a model for their voice and style and make the TTS service sound like them!

Analyzing Traffic Video Streams at Scale

This session demonstrates how to use the Transfer Learning Toolkit and pretrained models to build computer vision models and run inference on over 1,000 live video feeds on a single AWS instance powered by NVIDIA A100 GPUs.

Deploy Compute and Software Resources to Run AI/ML Applications in Azure Machine Learning with Just Two Commands

This session shows how to building a taxi fare prediction application using RAPIDS and shows how to automatically set up a DASK cluster with multiple Azure virtual machines to support large datasets, mount data into the Dask scheduler and workers, deploy GPU-optimized AI software from the NGC catalog to train models, and then make taxi fare predictions.

Build and Deploy AI Applications Faster on Azure Machine Learning

This session demonstrates the basics of Azure Machine Learning (AzureML) Platform, the benefits of using the NGC catalog, and how to leverage the NGC-AzureML Quick Launch Toolkit to build an end-to-end AI application in AzureML.

If you’re building an AI solution from scratch or just want to replicate the use cases shown in the above sessions, start with the NGC catalog.

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