Visual Studio Code Tools for AI is an extension to build, test, and deploy Deep Learning / AI solutions in Microsoft Visual Studio Code . This allows you to develop deep learning and AI solutions across Windows and MacOS
This extension seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not limited to submitting data preparation and model training jobs transparently to different compute targets. Additionally, it provides support for custom metrics and run history tracking, enabling data science reproducibility and auditing. Enterprise ready collaboration, allow to securely work on project with other people.
Because it's an IDE we've enabled familiar code editor features like syntax highlighting, IntelliSense (auto-completion) and text auto formatting. You can interactively test your deep learning application in your local environment using step-through debugging on local variables and models.
This extension makes it easy to train models on your local computer or you can submit jobs to the cloud by using our integration with Azure Machine Learning. You can submit jobs to different compute targets like Spark clusters, Azure GPU virtual machines and more
The extension provides several commands in the Command Palette for working with deep learning and machine learning:
To open the explorer, do as follow:
You can browse different samples and get more information about them. Let's browse until finding the "Classifying Iris" sample.
To create a new project based on this sample do the following:
The project will then be created.
Submitting a job to train your model locally or in the cloud
You will need to be logged-in to access your Azure resource. From the embedded terminal enter "az login" and follow the instruction.
Now that the new project is open in Visual Studio Code, you can submit a model training job to your different compute targets (local or VM with docker such as the https://azuremarketplace.microsoft.com/en-us/marketplace/apps/microsoft-ads.linux-data-science-... ).
Visual Studio Code Tools for AI provides multiple ways to submit a model training job.
Open iris_sklearn.py, right click and select Machine Learning: Submit Job .
If it is the first time your submit a job, you receive a message "No Machine Learning configuration found, creating...". A JSON file is opened, save it ( Ctrl+S ).
Once the job is submitted, the embedded-terminal displays the progress of the runs.View recent job performance and details
Once the jobs are submitted, you can list the jobs from the run history.
The Job List View opens and displays all the runs and some related information.
To view the results of a job, click on the job ID link to see detailed information.
See the key announcements from Ignite 2017 https://myignite.microsoft.com
Joseph Sirosh, Corporate Vice President of the Cloud AI Platform, as he dives deep into the latest additions to the Microsoft AI platform and capabilities. Innovations in AI let any developer and data scientist infuse intelligence into their applications and target entirely new scenarios. https://myignite.microsoft.com/videos/56555
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