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

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