Introduction
In this module, you'll learn how to create a labeled dataset using Azure Machine Learning data labeling tools. Azure Machine Learning studio makes it easy to perform and manage labeling tasks to prepare your data for model training. Once your data is made accessible to these tools, intuitive functionality allows you to get started right away.
Prerequisites
Scenario: Create a labeled dataset using Azure Machine Learning data labeling tools
You're a data scientist who has been assigned the task of improving automation in a manufacturing facility using computer vision. Azure Machine Learning studio was recently chosen as the development environment for managing the development of Machine Learning projects in your organization. You work in a team that plans to use features of this platform to collaborate on gathering and labeling of image data to produce a training set for use in development of a custom object detection model. Previously, your raw data was made accessible using a secure Datastore and it's now ready to undergo the task of labeling.
What will you learn?
After you finish this module, you'll be able to:
- Create a Dataset of labeled images retrieved from an attached Datastore
- Coordinate data, labels, and team members to efficiently manage and process labeling tasks
- Track progress and maintain a queue of incomplete labeling tasks
- Review labeled data and export as an Azure Machine Learning Dataset
What is the main goal?
This module will show you how to use data labeling tools to train custom object detection models in Azure Machine Learning studio.