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Hands-On Machine Learning with Azure

You're reading from  Hands-On Machine Learning with Azure

Product type Book
Published in Oct 2018
Publisher Packt
ISBN-13 9781789131956
Pages 340 pages
Edition 1st Edition
Languages
Authors (5):
Thomas K Abraham Thomas K Abraham
Profile icon Thomas K Abraham
Parashar Shah Parashar Shah
Profile icon Parashar Shah
Jen Stirrup Jen Stirrup
Profile icon Jen Stirrup
Lauri Lehman Lauri Lehman
Profile icon Lauri Lehman
Anindita Basak Anindita Basak
Profile icon Anindita Basak
View More author details
Toc

Table of Contents (14) Chapters close

Preface 1. AI Cloud Foundations 2. Data Science Process 3. Cognitive Services 4. Bot Framework 5. Azure Machine Learning Studio 6. Scalable Computing for Data Science 7. Machine Learning Server 8. HDInsight 9. Machine Learning with Spark 10. Building Deep Learning Solutions 11. Integration with Other Azure Services 12. End-to-End Machine Learning 13. Other Books You May Enjoy

Deploying an Azure AI Gallery template

Developing models with ML Studio does not have to be done from scratch. Azure AI Gallery contains a wide selection of templates for many different scenarios. These scenarios include many common use cases for ML, such as credit risk prediction, demand estimation, and text sentiment analysis. Templates can be imported to an Azure ML Studio Workspace with a few clicks and they contain all the steps needed to produce a working ML model. Studying templates is a great way to learn about different use cases and the steps required to produce an ML model. Some templates are prepared by Microsoft, but users can also submit their own experiments to the gallery.

The template gallery can be accessed directly from ML Studio. Open the ML Studio UI (as described previously) and create a new experiment by clicking on the + New in the bottom-left corner. This...

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