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|a QA76.585
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| 100 |
1 |
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|a Deza, Alfredo
|e presenter
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|a Azure remote compute for VSCode
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| 250 |
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|a [First edition]
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| 260 |
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|a [Place of publication not identified]
|b Pragmatic AI Solutions
|c 2022
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| 300 |
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|a 1 video file (29 min.)
|b sound, color
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| 653 |
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|a Infonuagique
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|a Web services / fast / (OCoLC)fst01173242
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|a Cloud computing / http://id.loc.gov/authorities/subjects/sh2008004883
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|a Web services / http://id.loc.gov/authorities/subjects/sh2003001435
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|a Windows Azure / http://id.loc.gov/authorities/names/n2010028313
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|a Services Web
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|a Cloud computing / fast / (OCoLC)fst01745899
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|a Windows Azure / fast / (OCoLC)fst01796039
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|a eng
|2 ISO 639-2
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|b OREILLY
|a O'Reilly
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|u https://learning.oreilly.com/videos/~/50126VIDEOPAIML/?ar
|x Verlag
|3 Volltext
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|a 004.6782
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|a Step up your local setup by setting a remote compute instance with attached SMB storage and then connect your local VSCode editor so that you can execute code and Jupyter Notebooks remotely. In this video I go through everything you need to know to crete a compute instance in Azure, both in Azure Machine Learning Studio and using the Data Science Virtual Machine spot instance that allows you to save costs when running a high memory with GPU instance. Because remote compute instances in the cloud should be considered ephemeral, specially if you are using spot instances, this video also covers setting up a storage account and a file share configuration for a Samba share that allows you to attach that same storage to any compute. Topics include: Create an Azure compute instance Learn about Spot Instances and other cost savings Setup VSCode for remote code execution Create an SMB file share and attach it to a VM Execute Jupyter Notebooks remotely Useful links: * Github Repository with summary instructions * Create a File share documentation on Azure * Data Science VMs in Azure
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