Awesome
Visual Studio Tools for AI
Visual Studio Tools for AI is an extension to build, test, and deploy Deep Learning / AI solutions. It seamlessly integrates with Cloud AI services such as 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, allows to securely work on projects with other people.
Get started with deep learning using Microsoft Cognitive Toolkit (CNTK), Google TensorFlow, PyTorch, Apache MXNet or other frameworks today.
Quick Links
Getting Started
- Release notes
- Installation
- Prepare development environment
- Deep learning sample recipes
- Frequently Asked Questions
Quickstarts
- Quick start from Start Page
- Tensorflow + Python
- Create AI project from Azure Machine Learning gallery
- Create AI project from existing code
- Create AI project from template
- Create AI project from samples repository
Tutorials
- Monitor & Visualize with TensorBoard
- Monitor Job History
- Manage Storage
- Monitor GPU Utilization
- TensorFlow + Azure Deep Learning VM
- Infuse AI into Your apps with Microsoft Cognitive Services
- Build Intelligent Apps with Pre-trained AI Models
- Convert Trained Models to ONNX
- View Network Architecture and Parameters of AI Models
Supported Operating Systems
Visual Studio Tools for AI only supports 64-bit Windows operating systems. Windows 10 is recommended for the best compatibility.
Supported Visual Studio versions
Visual Studio Tools for AI works with both Visual Studio 2017 and 2015 on Windows. Community, Professional and Enterprise editions are supported.
This extension is hosted on Visual Studio MarketPlace in two VS 2017, and VS 2015 packages. When downloading, the package file name may incorrectly end with ".zip". Please save it as ".vsix" and then install locally.
For the Visual Studio Code version please see Visual Studio Code Tools for AI
Develop, debug and deploy deep learning models and AI solutions
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.
Learn more about creating deep learning projects in Visual Studio
Get started quickly with the Start Page
Tools for AI Start Page is built to accelerate your start in AI world with
- Easy instructions to guide you to build your first AI application within 3 steps;
- AI inferencing/training samples and AI related learning materials for you to quickly learn and build your own AI solutions.
Moreover, Visual Studio Tools for AI is integrated with Azure Machine Learning to make it easy to browse through a gallery of sample experiments using CNTK, TensorFlow, MMLSpark and more.
Learn more about creating projects from the sample gallery
Scale out deep learning model training and/or inferencing to the cloud
Visual Studio Tools for AI 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
Learn more about training models in the cloud
Infuse AI into your apps with Microsoft Cognitive Services
Microsoft Cognitive Services are a set of APIs, SDKs and services available to developers to make your applications more intelligent, engaging and discoverable, with just a few lines of code. Visual Studio Tools for AI now easily enables you to discover, create and customize your cognitive services from within Visual Studio.
Learn more about working with Microsoft Cognitive Services
Build intelligent apps using pre-trained AI models
Building intelligent applications in Visual Studio is as easy as adding your pre-trained model to your app, just like any other library or resource. Visual Studio Tools for AI includes the Microsoft.ML.Scoring library that offers simplified consistent APIs across TensorFlow and ONNX models.
Moreover, Visual Studio Tools for AI generates a C# stub class to simplify interaction with models in your app. These Model Inference Library projects can be further deployed as NuGet packages for convenient distribution.
Learn more about using pre-trained AI models
Interoperation between different AI frameworks through model file conversion
There have been many AI frameworks for users to build their own models. However, they differ with each other greatly on the implementation details. This will inevitably result in that models produced by one framework cannot be reused for subsequent training or inference in another framework, which brings inconvenience and increases cost to users on framework choice. Model file conversion is a feasible trial towards such challenge.
Visual Studio Tools for AI now easily enables you to convert Core ML, TensorFlow, scikit-learn, XGBoost and LIBSVM models to ONNX format by leveraging existing model converters.
Learn more about model file conversion
Support
Support for this extension is provided on our GitHub Issue Tracker. You can submit a bug report, a feature suggestion or participate in discussions.
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
Privacy Statement
The Microsoft Enterprise and Developer Privacy Statement describes the privacy statement of this software.
License
This extension is subject to the terms of the End User License Agreement