Azure Data Scientist Associate: Machine Learning Orchestration & Deployment
Azure 2021 | Intermediate
- 11 videos | 1h 12m 57s
- Includes Assessment
- Earns a Badge
Azure Machine Learning Studio provides DevOps support in the form of orchestrating machine learning pipelines. In this course, you'll learn to create, publish, and schedule machine learning pipelines. First, you'll examine Azure Machine Learning pipelines and how they are used to build, optimize, and manage machine learning workflows. Next, you'll explore how to use the Azure Machine Learning SDK to create and run machine learning pipelines. You'll learn how to use a pipeline to import, transform, and move data between steps, as well as how to publish and track pipelines and use triggers to schedule a machine learning pipeline based on some event. Finally, you'll learn techniques for troubleshooting and debugging machine learning pipelines This course is one in a collection that prepares learners for the Designing and Implementing a Data Science Solution on Azure (DP-100) exam.
WHAT YOU WILL LEARN
discover the key concepts covered in this coursedescribe Azure Machine Learning pipelines and how they are used to build, optimize, and manage machine learning workflowsuse Azure Machine Learning pipelines to import, transform, and move data between stepsuse the Azure Machine Learning SDK to create and run machine learning pipelinespublish and track Machine Learning pipelines and share them with othersschedule a Machine Learning pipeline based on an elapsed time or file system changes
describe techniques for troubleshooting and debugging Machine Learning pipelinesdeploy a model as a real-time service to different compute targetsconsume a real-time service that can be used to predict labelstroubleshoot a failed deployment using various techniquessummarize the key concepts covered in this course
IN THIS COURSE
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