Episode 046 - Computer Vision on AWS with Francesco Pochetti – Part 2

Jul 29, 2022

Francesco Pochetti, Senior Machine Language Engineer at Bolt, dives deep into ML tools on AWS, such as NVIDIA Triton and TensorRT, improving processing time for Computer Vision. He also covers Amazon SageMaker, deploying ML models using Docker, and the importance of understanding the business problem when developing a machine learning model.

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Introduction

00:00 • 3min

Performing Image Segmentation on the Face with a Model

02:38 • 2min

Partnership between NVIDIA and AWS for efficient code running and deployment

04:42 • 4min

Deploying Models with Docker

08:52 • 6min

Understanding the Business Problem

14:33 • 15min

In part two, Dave chats again with Francesco Pochetti, Senior Machine Language Engineer at Bolt, and an AWS Machine Learning Hero. In this episode, Francesco dives deep in the ML tools on AWS, starting with the tools such as NVIDIA Triton and TensorRT, and how to improve processing time for Computer Vision. He also covers Amazon SageMaker, and many other AWS ML services as well as deploying ML models using Docker in the best way possible. If you missed it, you could listen to part one of this conversation in Episode 045. Francesco on Twitter: https://twitter.com/Fra_Pochetti Dave on Twitter: https://twitter.com/thedavedev Francesco’s Website: https://francescopochetti.com/ Francesco’s LinkedIn: https://www.linkedin.com/in/francescopochetti/ Francesco’s GitHub: https://github.com/FraPochetti [BLOG] Blurry faces: Training, Optimizing and Deploying a segmentation model on Amazon SageMaker with NVIDIA TensorRT and NVIDIA Triton - https://francescopochetti.com/blurry-faces-a-journey-from-training-a-segmentation-model-to-deploying-tensorrt-to-nvidia-triton-on-amazon-sagemaker/ [BLOG] Machine Learning and Developing inside a Docker Container in Visual Studio Code https://francescopochetti.com/developing-inside-a-docker-container-in-visual-studio-code/ [BLOG] Deploying a Fashion-MNIST web app with Flask and Docker: https://francescopochetti.com/deploying-a-fashion-mnist-web-app-with-flask-and-docker/ [BLOG] IceVision meets AWS: detect LaTeX symbols in handwritten math and deploy with Docker on Lambda: https://francescopochetti.com/icevision-meets-aws-detect-latex-symbols-in-handwritten-math-and-deploy-with-docker-on-lambda/ [DOCS] Amazon Rekognition - https://aws.amazon.com/rekognition/ [DOCS] Amazon SageMaker - https://aws.amazon.com/sagemaker/ [DOCS] Amazon Textract - https://aws.amazon.com/textract/ [DOCS] Deploy fast and scalable AI with NVIDIA Triton Inference Server in Amazon SageMaker https://aws.amazon.com/blogs/machine-learning/deploy-fast-and-scalable-ai-with-nvidia-triton-inference-server-in-amazon-sagemaker/ [GIT] Nvidia Triton Inference Server: https://github.com/triton-inference-server/server/ [GIT] Blurry faces: Training, Optimizing and Deploying a segmentation model on Amazon SageMaker with NVIDIA TensorRT and NVIDIA Triton - https://github.com/FraPochetti/KagglePlaygrounds/tree/master/triton_nvidia_blurry_faces Subscribe: Amazon Music: https://music.amazon.com/podcasts/f8bf7630-2521-4b40-be90-c46a9222c159/aws-developers-podcast Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-developers-podcast/id1574162669 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zb3VuZGNsb3VkLmNvbS91c2Vycy9zb3VuZGNsb3VkOnVzZXJzOjk5NDM2MzU0OS9zb3VuZHMucnNz Spotify: https://open.spotify.com/show/7rQjgnBvuyr18K03tnEHBI TuneIn: https://tunein.com/podcasts/Technology-Podcasts/AWS-Developers-Podcast-p1461814/ RSS Feed: https://feeds.soundcloud