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1. Citrix Workspace app 2006.1 for Windows. Citrix Workspace app 2002 for Windows. Citrix Workspace app 1911 for Windows.
2. Using Workspaces.; 2 minutes to read; In this article. When you exit WinDbg, it saves your session configuration in a workspace. A workspace enables you to easily preserve your settings from one session to another. You can also save or clear the workspaces manually, or even use a workspace to save a debugging session that is still in.

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2. Workspaces 1 3 2 =
3. Workspaces 1 3 2 Player Games

2 Workspace Menu Options. 2.1 Open Files; 2.2 Open PDB File from RCSB Protein Data Bank; 3 Workspace Data Node Menu Options. 3.1 Save; 3.2 Export to tab-delim; 3.3 Rename; 3.4 Remove; 4 Data Node Hover-text Information; 5 Workspaces. 5.1 Saving the Workspace. 5.1.1 Special considerations on saving and restoring workspaces; 5.2 Opening a Saved.

Workspace is a term used in various branches of engineering and economic development.

Business development[edit]

Workspace refers to small premises provided, often by local authorities or economic development agencies, to help new businesses to establish themselves. These typically provide not only physical space and utilities but also administrative services and links to support and finance organizations, as well as peer support among the tenants. A continuum of sophistication ranges through categories such as 'managed workspaces', 'business incubators' and 'business and employment co-operatives'. In cities, they are often set up in buildings that are disused but which the local authority wishes to retain as a landmark. At the larger end of the spectrum are business parks, virtual offices, technology parks and science parks.

Technology and software[edit]

In technology and software, 'workspace' is a term used for several different purposes.

Software development[edit]

A workspace is (often) a file or directory that allows a user to gather various source code files and resources and work with them as a cohesive unit.^[1] Often these files and resources represent the complete state of an integrated development environment (IDE) at a given time, a snapshot. Workspaces are very helpful in cases of complex projects when maintenance can be challenging. Good examples of environments that allow users to create and use workspaces are Microsoft Visual Studio and Eclipse.

In configuration management, 'workspace' takes on a different but related meaning; it is a part of the file system where the files of interest (for a given task like debugging, development, etc.) are located. It stores the user's view of the files stored in the configuration management's repository.

In either case, workspace acts as an environment where a programmer can work, isolated from the outside world, for the task duration.^{[citation needed]}

Graphical interfaces[edit]

Additionally, workspaces refer to the grouping of windows in some window managers. Grouping applications in this way is meant to reduce clutter and make the desktop easier to navigate.

Multiple workspaces are prevalent on Unix-likeoperating systems and certain operating system shells. Mac OS X 10.5 and later macOS releases include an equivalent feature called 'Spaces'. Windows 10 now offers a similar feature called 'Task View'.Windows XPPowerToy is available to bring this functionality to Windows XP.

Most systems with support for workspaces provide keyboard shortcuts to switch between them. Many also include some form of workspace switcher to change between them and sometimes to move windows between them as well.

Workspaces are visualized in different ways. For example, on Linux computers using Compiz or Beryl with the Cube and Rotate Cube plugins enabled, each workspace is rendered as a face of an on-screen cube, and switching between workspaces is visualized by zooming out from the current face, rotating the cube to the new face, and zooming back in. On macOS, the old set of windows slides off the screen and the new set slides on. Window managers without 'eye candy' often simply remove the old windows and display the new ones without any sort of intermediate effect.

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Computer-supported cooperative work[edit]

In the context of computer-supported cooperative work (CSCW) a shared workspace is a place of collaboration that enables group awareness.'A shared workspace provides a sense of place where collaboration takes place. It is generally associated with some part of the screen real estate of the user's computer where the user ‘‘goes'' to workon shared artifacts, discovers work status, and interacts with his/her collaborators.'^[2] Pdf expert edit and sign pdf 2 4 5.

Online applications[edit]

In the context of software as a service, 'workspace' is a term used by software vendors for applications that allow users to exchange and organize files over the Internet.^{[citation needed]}

Such applications have several advantages over traditional FTP clients or virtual folder offerings, including:^{[citation needed]}

• Ability to capture task performance data and version data
• Organization of information in a more user-friendly interface than a traditional file-based structure
• Secure storage and upload/download of data (many FTP clients are unsecured, susceptible to eavesdropping, or open to other abuse)
• Compatible with virtually all web browsers and computer operating systems.
• Updated on the server-side, meaning that a user will never have to update the software.

Beyond organizing and sharing files, these applications can often also be used as a business communication tool for assigning tasks, scheduling meetings, and maintaining contact information.

Robotics[edit]

In Robotics, the workspace of a robot manipulator is often defined as the set of points that can be reached by its end-effector^{[citation needed]} or, in other words, it is the space in which the robot works and it can be either a 3D space or a 2D surface.

Mobile or unified workspace[edit]

A mobile or unified workspace allows enterprise IT to have a trusted space on any device where IT can deliver business applications and data.

Ever since the iPad was released by Apple in 2009, bring your own device (BYOD) has become an increasingly more important problem for IT.^[3] Until now, IT has purchased, provisioned, and managed all enterprise desktops which run the Microsoft Windows software.^[4] There are nearly 500 million enterprise desktops in the world. However, with the introduction of smartphones and tablets, there are far more devices that are owned by the end-user - 750 million PCs and Macs, 1.5 billion smartphones, and 500 million tablets. These also run different operating systems, like iOS, Android, Windows, and macOS. How does deliver business applications and data to end-users on these heterogeneous operating systems and form factors?

Federica Troni^[5] and Mark Margevicius^[6] introduced the concept of Workspace Aggregator^[7] to solve the problem of BYOD. According to Gartner, a workspace aggregator unifies five capabilities:(1) Application Delivery: The ability to orchestrate provisioning and de-provisioning of mobile, PC and Web applications(2) Data: The secure delivery of corporate data(3) Management: Management of application life cycle, metering, and monitoring features(4) Security: Provision of context-aware security(5) User Experience: A superior user experience through the delivery of a unified workspace

References[edit]

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1. ^M. Lloyd, Catherine. Encyclopedia of Systems Biology: Workspace (1 ed.). Springer. p. 2356. doi:10.1007/978-1-4419-9863-7_1531. ISBN978-1-4419-9863-7.
2. ^Wiley Encyclopedia of Computer Science and Engineering (1 ed.). John Wiley & Sons, Inc. 2008. p. D-2. ISBN9780471383932.
3. ^Kingsley-Hughes, Adrian. 'Making BYOD work: The art of compromise - ZDNet'. zdnet.com. Retrieved 30 April 2018.
4. ^http://www.workspot.com/wp-content/uploads/2014/02/Workspot-Technology-White-Paper-.pdf
5. ^http://www.gartner.com/AnalystBiography?authorId=10906
6. ^http://www.gartner.com/AnalystBiography?authorId=13910
7. ^'An Overview of Workspace Aggregators'. www.gartner.com. Retrieved 30 April 2018.

The workspace is the top-level resource for Azure Machine Learning, providing a centralized place to work with all the artifacts you create when you use Azure Machine Learning. The workspace keeps a history of all training runs, including logs, metrics, output, and a snapshot of your scripts. You use this information to determine which training run produces the best model.

Once you have a model you like, you register it with the workspace. You then use the registered model and scoring scripts to deploy to Azure Container Instances, Azure Kubernetes Service, or to a field-programmable gate array (FPGA) as a REST-based HTTP endpoint. You can also deploy the model to an Azure IoT Edge device as a module.

Taxonomy

A taxonomy of the workspace is illustrated in the following diagram:

The diagram shows the following components of a workspace:

• A workspace can contain Azure Machine Learning compute instances, cloud resources configured with the Python environment necessary to run Azure Machine Learning.

• User roles enable you to share your workspace with other users, teams, or projects.

• Compute targets are used to run your experiments.

• When you create the workspace, associated resources are also created for you.

• Experiments are training runs you use to build your models.

• Pipelines are reusable workflows for training and retraining your model.

• Datasets aid in management of the data you use for model training and pipeline creation.

• Once you have a model you want to deploy, you create a registered model.

• Use the registered model and a scoring script to create a deployment endpoint.

Tools for workspace interaction

You can interact with your workspace in the following ways:

Important

Tools marked (preview) below are currently in public preview.The preview version is provided without a service level agreement, and it's not recommended for production workloads. Certain features might not be supported or might have constrained capabilities.For more information, see Supplemental Terms of Use for Microsoft Azure Previews.

• On the web:
• In any Python environment with the Azure Machine Learning SDK for Python.
• In any R environment with the Azure Machine Learning SDK for R (preview).
• On the command line using the Azure Machine Learning CLI extension

Machine learning with a workspace

Machine learning tasks read and/or write artifacts to your workspace.

• Run an experiment to train a model - writes experiment run results to the workspace.
• Use automated ML to train a model - writes training results to the workspace.
• Register a model in the workspace.
• Deploy a model - uses the registered model to create a deployment.
• Create and run reusable workflows.
• View machine learning artifacts such as experiments, pipelines, models, deployments.
• Track and monitor models.

Workspace management

Dropzone 4 pro 4 0 24. You can also perform the following workspace management tasks:

Warning

Moving your Azure Machine Learning workspace to a different subscription, or moving the owning subscription to a new tenant, is not supported. Doing so may cause errors.

Create a workspace

There are multiple ways to create a workspace:

• Use the Azure portal for a point-and-click interface to walk you through each step.
• Use the Azure Machine Learning SDK for Python to create a workspace on the fly from Python scripts or Jupiter notebooks
• Use an Azure Resource Manager template or the Azure Machine Learning CLI when you need to automate or customize the creation with corporate security standards.
• If you work in Visual Studio Code, use the VS Code extension.

Associated resources

When you create a new workspace, it automatically creates several Azure resources that are used by the workspace:

• Azure Storage account: Is used as the default datastore for the workspace. Jupyter notebooks that are used with your Azure Machine Learning compute instances are stored here as well.

  Important

  By default, the storage account is a general-purpose v1 account. You can upgrade this to general-purpose v2 after the workspace has been created.Do not enable hierarchical namespace on the storage account after upgrading to general-purpose v2.

  To use an existing Azure Storage account, it cannot be a premium account (Premium_LRS and Premium_GRS). It also cannot have a hierarchical namespace (used with Azure Data Lake Storage Gen2). Neither premium storage or hierarchical namespaces are supported with the default storage account of the workspace. You can use premium storage or hierarchical namespace with non-default storage accounts.

• Azure Container Registry: Registers docker containers that you use during training and when you deploy a model. To minimize costs, ACR is lazy-loaded until deployment images are created.

• Azure Application Insights: Stores monitoring information about your models.

• Azure Key Vault: Stores secrets that are used by compute targets and other sensitive information that's needed by the workspace.

Note

In addition to creating new versions, you can also use existing Azure services.

What happened to Enterprise edition

As of September 2020, all capabilities that were available in Enterprise edition workspaces are now also available in Basic edition workspaces.New Enterprise workspaces can no longer be created. Any SDK, CLI, or Azure Resource Manager calls that use the sku parameter will continue to work but a Basic workspace will be provisioned.

Beginning December 21st, all Enterprise Edition workspaces will be automatically set to Basic Edition, which has the same capabilities. No downtime will occur during this process. On January 1, 2021, Enterprise Edition will be formally retired.

In either editions, customers are responsible for the costs of Azure resources consumed and will not need to pay any additional charges for Azure Machine Learning. Please refer to the Azure Machine Learning pricing page for more details.

Workspaces 1 3 2 Player Games

Next steps

To get started with Azure Machine Learning, see: