Microsoft Cloud Workshop (MCW) is a hands-on community development experience. Microsoft Cloud Workshop (MCW) is a hands-on community development experience. Use the following filters to search our database of Microsoft Cloud Workshop materials. Each workshop includes presentation decks, trainer and student guides, and hands-on lab guides. Design a modernization plan to move services from on-premises to the cloud by leveraging cloud, web, and mobile services, secured by Azure Active Directory.
This book is written for Windows professionals who are familiar with PowerShell and want to learn to build, operate, and administer their Windows workloads in the Microsoft Azure cloud. Pro PowerShell for Microsoft Azure is packed with practical examples and scripts, with easy-to-follow explanations for a wide range of day-to-day needs and essential administration tasks. Author Sherif Talaat begins by explaining the fundamental concepts behind the Microsoft Azure platform and how to get started configuring it using PowerShell. Readers will find out how to deploy, configure, and manage the various components of the Azure platform, from storage and virtual networks to HDInsight clusters. Workload automation, scheduling, and resource management are covered in depth to help build efficiency in everyday tasks, and administrators will gain full control over Azure identity and access rights.
Imagine reducing your training time for an epoch from 30 minutes to 30 seconds, and testing many different hyper-parameter weights in parallel. Available now, in public preview, Batch AI is a new service that helps you train and test deep learning and other AI or machine learning models with the same scale and flexibility used by Microsoft's data scientists. Managed clusters of GPUs enable you to design larger networks, run experiments in parallel and at scale to reduce iteration time and make development easier and more productive. Spin up a cluster when you need GPUs, then turn them off when you're done and stop the bill. Developing powerful AI involves combining large data sets for training with clusters of GPUs for experimenting with network design and optimization of hyper-parameters.