Tag Archives: manage

Difference between Azure Machine Learning Studio vs. Workbench vs Azure Machine Learning Services?


When introduced Azure Machine Learning Workbench was a preview downloadable application. It provides a UI for many of the Azure Machine Learning CLI commands, particularly around experimentation submission for Python based jobs to DSVM or HDI. The Azure Machine Learning CLI is made up of many key functions, such as job submission, and creation of real time web services. The workbench installer provided a way to install everything required to participate in the preview.

Azure Machine Learning Studio is an older product, and provides a drag and drop interface for creating simply machine learning processes. It has limitations about the size of the data that can be handled (about 10gigs of processing). Learning and customer requests have based on this service have contributed to the design of the new Azure Machine Learning CLI mentioned above. BTW, now it should be added that Azure Machine Learning Workbench is deprecated since September 2018 and has been replaced by the Azure Machine Learning services (now GA).

Azure Machine Learning Service

The core functionality is still intact, but some major changes to point out about the architecture are:

  • A simplified Azure resources model
  • New portal UI to manage your experiments and compute targets
  • A new, more comprehensive Python SDK
  • A new expanded Azure CLI extension for machine learning

So in short, Azure Machine Learning service contains many advanced capabilities designed to simplify and accelerate the process of building, training, and deploying machine learning models. Automated machine learning enables data scientists of all skill levels to identify suitable algorithms and hyperparameters faster. Support for popular open-source frameworks such as PyTorch, TensorFlow, and scikit-learn allow data scientists to use the tools of their choice. DevOps capabilities for machine learning further improve productivity by enabling experiment tracking and management of models deployed in the cloud and on the edge. All these capabilities can be accessed from any Python environment running anywhere, including data scientists’ workstations.

Training: Microsoft Azure IaaS Deep Dive Jump start


If you havent’ looked at this training, then I would recommend you to have a get a broad overview of the cloud, along with working definitions of infrastructure as a service (IaaS) and platform as a service (PaaS). The experts also discuss portals, subscription, costs, and Azure data centers. Using this training you can learn how to integrate Windows Azure virtual machines (VMs) into your infrastructure. If you’re an experienced IT Pro but you haven’t spent much time with Windows Azure VMs, you’ll appreciate these real-world examples on Windows Azure infrastructure as a service (IaaS).

Cheryl McGuire and Ronald Beekelaar walk you through the basics of creating and configuring VMs, virtual networks, and cross-premises communication. They discuss the “what, why, and how” of virtualization, along with details about managing VMs, how they behave in Windows Azure, and how to configure good network communication to get things up and running in the cloud. 

https://mva.microsoft.com/en-US/training-courses-embed/microsoft-azure-iaas-deep-dive-jump-start-8287/-Azure-Virtual-Machines-S1oXqFXy_2804984382

Happy deep diving!!

Azure Dev TestLabs for Developers and testers…


Azure DevTest Labs provides developers and testers a self-service sandbox environment to quickly create Dev/Test environments while minimizing waste and controlling costs. This lab provides lot of benefits including creating, configuring, and managing developer and test environments in the Azure cloud.

Using this service the developers and testers quickly create environments in Azure while minimizing waste and controlling cost. You can test the latest version of your application by quickly provisioning Windows and Linux environments using reusable templates and artifacts. Easily integrate your deployment pipeline with DevTest Labs to provision on-demand environments. Scale up your load testing by provisioning multiple test agents, and create pre-provisioned environments for training and demos.

 

https://channel9.msdn.com/Blogs/Windows-Azure/What-is-Azure-DevTest-Labs/player

You can get it started from here. To create a Dev Testlabs lab, you will need:

Hope this helps!!

Free Jump Start course – Core Solutions on Microsoft Exchange Server 2013


Are you planning an upgrade to Microsoft Exchange Server 2013, or do you want to know more about what it would involve? Would you like help preparing for Exam 70-341 or Exam 70-342? Take this fast-paced, demo-rich Jump Start course, and learn about planning, deploying, and managing Microsoft Exchange Server 2013 Exchange on-premises.

You’ll find out how to manage the messaging infrastructure and provide high availability and security through demos geared to your business needs. This Jump Start is appropriate for anyone upgrading from earlier versions of Exchange, and gives as well as IT Pros who have prior networking experience the Microsoft Exchange training they need. You can visit Microsoft Virtual Academy’s Core Solutions of Exchange Server 2013 Jump Start.

This Jump Start is appropriate for anyone upgrading from earlier versions of Exchange as well as IT Pros new to Exchange but with prior networking experience. If you are pursuing the MCSE: Messaging certification, it will help you prepare for Exam 70-341.

https://channel9.msdn.com/Series/Core-Solutions-Exchange-2013/01/player

Full course outline:

  • Mod 01: Deploying and Managing Microsoft Exchange Server 2013
  • Mod 02: Configuring Mailbox Servers and Recipients
  • Mod 03: Deploying and Managing Client Access Servers and Clients
  • Mod 04: Configuring the Message Transport
  • Mod 05: Implementing High Availability and Disaster Recovery
  • Mod 06: Configuring Administrative Security and Auditing
  • Mod 07: Migrating to Microsoft Exchange Server 2013

So, make use of it Smile

AD article: Managing multiple Active Directory schemas


Each Active Directory forest has its own schema, which defines the objects and attributes that the directory service uses to store data.

When organizations have multiple Active Directory forests, IT administrators have to manage multiple Active Directory schemas; ensuring consistency between schemas is vital when managing multiple forests.

In the April issue of TechNet Magazine, John Policelli guides you through a streamlined process to manage multiple Active Directory schemas.

Read the full article online now.