Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Getting Started with Visual Studio Tools for AI
1.
2.
3. Integrated w/Azure Machine Learning
Integrated w/Cognitive Services
Create new deep learning projects easily
Scale Out with Azure Batch AI
Generate C# code from TensorFlow & ONNX models
Convert models to ONNX
Monitor model training progress & GPU utilization
Visualize your model training with TensorBoard
Get started quickly with the Samples Gallery
Visual Studio Tools for AI
AI developer tool to train models & infuse AI into your apps
http://aka.ms/vstoolsforai http://aka.ms/vscodetoolsforai
17. Creating Art with Image Style Transfer Models
Data Sources Ingest / Prepare Model Train with Cloud AI Deploy Consume
AC TION
INTELLIGENC EDATA
Azure Blob
Raw storage
Azure Machine
Learning
Docker Image + IoT Hub
Model Update +
Manageability
10
01
Model: VGG-19
Code:
Tensorflow and
Keras
Microsoft
Common Objects in Context
(COCO)
328k images
91 different types of objects
could be recognized by a 4 year old
Visual Studio
Tools for AI
Deep Learning
Virtual Machine
(DLVM)
18. • We want to preserve stylistic features but not spatial structure
• Loss functions measure high-level perceptual and semantic differences between
images
• Use pretrained loss network called VGG-19 trained on the ImageNet dataset
Creating Art with Image Style Transfer Models
Inspired by “Perceptual Losses for Real-Time Style Transfer and Super-Resolution”
https://arxiv.org/abs/1603.08155
Approach (see paper for more detail) What’s happening inside
19. Create new deep learning projects easily
Use TensorFlow, CNTK, Keras, Caffe2, Chainer, and more.
Debug and iterate quickly with the power of Visual Studio.
20. Integrated with Azure Machine Learning
Get started quickly with the sample gallery.
Manage your experiments and models. Deploy in the cloud or on the edge.
21. Scale Out with Azure Batch AI
Elastically scale training in Azure. Select Docker container, # VMs per job.
Pay only for what you use when jobs are running.
22. Monitor model training progress & GPU utilization
Integrated with TensorBoard to easily monitor & visualize your model training.
GPU heatmap provides visibility for optimizing your resource utilization
23. Storage Browser to upload data, copy model & view logs
Easily upload data to remote machines, download model files and view logs
Working in the cloud is as convenient as your desktop.
24. Infuse AI into your apps today
Include model in your app like any other resource
… Or deploy to Azure ML and call via REST API
25.
26. Bringing the best of AI to Azure and the best of Azure to AI
Pre-Built AI
Azure Cognitive Services
Conversational AI
Azure Bot Service
Custom AI
Azure Machine Learning
27. Integrated w/Azure Machine Learning
Integrated w/Cognitive Services
Create new deep learning projects easily
Scale Out with Azure Batch AI
Generate C# code from TensorFlow & ONNX models
Convert models to ONNX
Monitor model training progress & GPU utilization
Visualize your model training with TensorBoard
Get started quickly with the Samples Gallery
Visual Studio Tools for AI
AI developer tool to train models & infuse AI into your apps
http://aka.ms/vstoolsforai http://aka.ms/vscodetoolsforai
28. find out more!
Learn more about
Cognitive Services – https://aka.ms/cogsvcs
Azure ML – https://aka.ms/azuremlbuild
Visual Studio Tools for AI - https://aka.ms/vstoolsforai
Deep Learning VMs - https://aka.ms/dlvmbuild
Batch AI – https://aka.ms/batchaibuild
ML.Net - https://docs.microsoft.com/en-us/dotnet/machine-learning/