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.openpublishing.publish.config.json

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docs/_breadcrumb/toc.yml

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docs/ai/TOC.yml

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# Auto-expanded node
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docs/ai/about-ai-tools.md

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Visual Studio Tools for AI is an extension to build, test, and deploy Deep Learning / AI solutions. It 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.
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Get started with deep learning using [Microsoft Cognitive Toolkit (CNTK)](https://docs.microsoft.com/cognitive-toolkit/), [Google TensorFlow](https://www.tensorflow.org), or other deep-learning frameworks today.
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Get started with deep learning using [Microsoft Cognitive Toolkit (CNTK)](/cognitive-toolkit/), [Google TensorFlow](https://www.tensorflow.org), or other deep-learning frameworks today.
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## Develop, debug, and deploy deep learning models and AI solutions
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Use the productivity features of Visual Studio to accelerate AI innovation today. Use built-in code editor features like syntax highlighting, IntelliSense, 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.

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title: Create an AI project from existing code
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title: Create a project
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Azure Machine Learning is integrated with Visual Studio Tools for AI. You can use it to submit machine learning jobs to remote compute targets like Azure virtual machines, Spark clusters, and more. Learn more about [Azure Machine Learning Experimentation](https://docs.microsoft.com/azure/machine-learning/preview/experimentation-service-configuration)
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> Azure Machine Learning Workbench must be installed.
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You can download the tools from the [Visual Studio Marketplace](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vstoolsai-vs2017), or from within Visual Studio:
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### TensorFlow
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