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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

Table of Contents (14) Chapters

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

Summary

As we have seen in this chapter, integrating Azure AI services with other non-AI services is easy and configuring these integrations can be done in a few simple steps. For codeless approach, Logic Apps and Data Factory provide tools to automate many data-related tasks. By leveraging AI services such as Cognitive Services or ML Studio Web Services, the incoming data can be enriched with insights and predictions produced by the AI services.

The trigger-based event handling system allows you to react to different kinds of events, for example when a new file is created or modified in cloud storage. The triggers can be used to launch data processing pipelines in scenarios where data moves infrequently and schedule-based data processing might introduce lags, since the system must wait for the scheduled time to lapse. With storage-based triggers, the data pipeline can be initiated...

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