Develop Custom Object Detection Models with NVIDIA and Azure Machine Learning

  • Learning Path
  • 4 Modules
Intermediate
AI Engineer
Data Scientist
Azure
Azure Storage
Azure Machine Learning

Azure Machine Learning studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure. Learn how to develop custom object detection models using this service with NVIDIA GPU accelerated virtual machines.

Prerequisites

Modules in this learning path

Create workspace resources for getting started with Azure Machine Learning

In this module, you learn how to create resources for getting started with Azure Machine Learning.

Create a labeled dataset using Azure Machine Learning data labeling tools

Learn how to use Azure Machine Learning data labeling to create, manage, and monitor data labeling projects.

Use AutoML to train a labeled dataset and develop a production model

Learn how to use Automated Machine Learning to train a labeled dataset and develop a production object detection model.

Deploy model to NVIDIA Triton Inference Server

NVIDIA Triton Inference Server is a multi-framework, open-source software that is optimized for inference. It supports popular machine learning frameworks like TensorFlow, Open Neural Network Exchange (ONNX) Runtime, PyTorch, NVIDIA TensorRT, and more. It can be used for your CPU or GPU workloads. In this module, you deploy your production model to NVIDIA Triton server to perform inference on a cloud-hosted virtual machine.