A static website featuring the sketchnotes from my Cloud Computing learning journeys - with relevant links to sources where possible

How to deploy ONNX models using DeepStream on Jetson Nano

SpiNNaker based Nengo simulator.

Open standard for machine learning interoperability

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Sample showing how to deploy a AI model from the Custom Vision service to a Raspberry Pi 3 device using Azure IoT Edge

Docker CLI plugin for extended build capabilities with BuildKit

Primary source of truth for the Docker "Official Images" program

AI Toolkit for Azure IoT Edge

Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.

Build and run Docker containers leveraging NVIDIA GPUs

The Azure IoT Edge product

The IoT Edge OSS project

Vision AI Developer Kit Preview

Embedded Learning Library

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

MobileNet_v1 modified to be Quantization Friendly per https://arxiv.org/abs/1803.08607

Tutorials for creating and using ONNX models

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

Easily deploy models to FPGAs for ultra-low latency with Azure Machine Learning powered by Project Brainwave

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft