Develop Custom Object Detection Models with NVIDIA and Azure Machine Learning

Description

In this course, you will learn:

• Create workspace resources to get started with Azure Machine Learning.
• Create a labeled dataset with Azure Machine Learning data labeling tools.
• Use AutoML to train a labeled dataset and create a production model.
• Deploy the model to the NVIDIA Triton Inference Server.

Syllabus:

• Create workspace resources for getting started with Azure Machine Learning
  • Introduction to Azure Machine Learning
  • Create an Azure Storage Account
  • Create an Azure Storage Container
  • Create an Azure Machine Learning Workspace
  • Create an Azure Machine Learning Compute Instance
  • Create an Azure Machine Learning Datastore
• Create a labeled dataset using Azure Machine Learning data labeling tools
  • Create an Azure Machine Learning data labeling project
  • Label images with Azure Machine Learning data labeling tools
  • Export a labeled Azure Machine Learning dataset
• Use AutoML to train a labeled dataset and develop a production model
  • Prepare the Jupyter notebook workspace
  • Configure the Jupyter notebook execution environment
  • Execute the Jupyter Notebook to produce an object detection model using AutoML
• Deploy model to NVIDIA Triton Inference Server
  • Create a GPU Accelerated Virtual Machine
  • Install prerequisites and NVIDIA Triton Inference Server
  • Execute inference workload on NVIDIA Triton Inference Server