Microsoft Build 2020 Expert Q&A: Cloud AI and Machine Learning Resources
By: Aaron, Ari
Tags: Machine Learning, Data Science, AI, Microsoft, Azure

Today at //MSBuild I hosted an Expert Q&A: Cloud AI and Machine Learning session on Microsoft Cloud AI and ML technologies. The following is a list of some of my answers to some of my favorite questions that I received.

If you have any other open questions or topics you want to learn more about in the AI/ML space be sure to comment below. If you are new to Azure you can get started a free subscription using the link below.

Questions Table Of Contents

What is your day to day like as an AI Cloud Advocate? Where can I get started learning AI/ML? Where can I find AI/ML case studies and examples? Do you know of any good resources to get started with Speech Synthesis and Classification? What cool ML/AI work have you seen regarding Covid-19? Is there any shortcut for identifying a model against a particular problem without doing extensive research on the data? For Quality Analysts/Quality Engineers that are new to ML, where would you recommend starting when learning how to validate/interpret models and/or validating the impact of applied ML? Do you have some insights to Azure ML Data labeling tool? Does it support (semi-auto) labeling methods? What about instance segmentation annotation? Is there a Template for CI/CD for Azure Custom Vision and Azure QnA Maker? I have a lot of documents in different formats Word, PDF, Image, Text how can I extract the text so that I can process them with AI/ML. Does Microsoft have any resources for Classification Aerial or Satellite Imagery Do you have any solutions coming to help with scarcity of initial data especially with computer vision and speech synthesis? How much experience do you have with deploying deep learning models on IoT/hardware devices and which products utilizes this the best right now? How will DeepStream integration with Azure IoT edge be supported and any upcoming features or modules for IoT edge? In your opinion when is it good to use Databricks and when is it good to use AzureML?

Expert Q&A: Cloud AI and Machine Learning Questions

1. What is your day to day like as an AI Cloud Advocate?

This is a great question. While no two days are exactly the same as a developer advocate I spend my time divided between the follow three areas:

Community — you’ll see me both offline (whether it’s conferences, meetups, and user groups) and online (from forums to open source projects and social media outlets) meeting and collaborating with you here in Israel. Content — we believe in the power of quality documentation. We listen to you and then directly contribute your feedback to making our documentation as empowering as possible.We also author blog posts, write articles, create videos, contribute to and create our own open source projects based on your needs. Engineering — at the end of the day, we are all engineers. We connect with developers in the field, foster strong relationships with teams at Microsoft, and work together to improve the experience of building solutions in the cloud.

I do things like:

Developing open source code to unblock you and provide inspiration.

Write blog posts and articles about topics I believe will help you accomplish more.

Ensure you have the best possible documentation available.

Learning from you at user groups and conferences.

Share learnings and updates with you at meetups and conferences.

Connecting with you over social media @pythiccoder.

Taking your feedback back to the correct product teams who can make a difference.

Listening and growing, every day.

For more information check out my post on the topic

2. Where can I get started learning AI/ML?

There are a lot of amazing places to get started with AI/ML if you ask me almost too many here are some of my favorite resources.

3. Where can I find AI/ML case studies and examples?

Microsoft provides some pretty great resources for our AI case studies I will link to a few of them below.

4. Do you know of any good resources to get started with Speech Synthesis and Classification?

For getting started I would recommend checking out the Azure Speech Cognitive service offering. We have some really nice getting started demos for creating Speech to Text, Text to Speech and custom voice applications.

To learn check more check out are documentation below.

5. What cool ML/AI work have you seen regarding Covid-19?

There have been some really creative AI/ML solutions in this space. I’ll link to a couple really interesting ones that Microsoft has been directly involved in.

Also check out this awesome dataset put together by AI2.

6. Is there any shortcut for identifying a model against a particular problem without doing extensive research on the data?

It is critical to get to know your data in order to build quality AI models how ever in order to better get to know your data it is worth experimenting with different architectures. For classical Machine Learning problems I recommend taking a look at the cheat sheet below.

But this is where in my opinion the Azure AutoML Service shines. With very little configuration and no code you can quickly test many model architectures to find a strong starting base line for your data.

For more information check out our documentation.

7. For Quality Analysts/Quality Engineers that are new to ML, where would you recommend starting when learning how to validate/interpret models and/or validating the impact of applied ML?

This is a great question I actually gave a presentation on this very topic just a few days ago (see below.)

While interpretability in machine learning is still an open area for research I’d recommend taking a look at the Microsoft Interpretability toolkit as a strong starting point.

Check out the documentation and getting started notebooks below to learn more.

I also have a good post on SHAP values that I’d recommend as well

One last area that is worth keeping an eye on is Data Drift we have some great tooling to help with this as well.

8. Do you have some insights to Azure ML Data labeling tool? Does it support (semi-auto) labeling methods? What about instance segmentation annotation?

With the release of Azure ML, Microsoft provided a new labeling tool that currently supports image and bounding box labeling.

The ML assisted labeling page lets you trigger automatic machine learning models to accelerate the labeling task and is supported in the Enterprise Azure ML Tier.

If you need instance segmentation or Video annotation support I suggest looking at the open source Microsoft VoTT tool.

9. Is there a Template for CI/CD for Azure Custom Vision and Azure QnA Maker?

Yes check out the resources below.

10. I have a lot of documents in different formats Word, PDF, Image, Text how can I extract the text so that I can process them with AI/ML.

This is a great question Microsoft put together a reference architecture for exactly this scenario using Cognitive Search . Check out the documentation and JFK example below.

Also check out the form Azure Form Recognizer Service.

11. Does Microsoft have any resources for Classification Aerial or Satellite Imagery

Yes check out the resources below.

12. Do you have any solutions coming to help with scarcity of initial data especially with computer vision and speech synthesis?

There are couple different approaches to handle scarcity of data from transfer learning from simulation, data augmentation, and one shot/ meta learning approaches I will provide some resources below.

13. How much experience do you have with deploying deep learning models on IoT/hardware devices and which products utilizes this the best right now?

I have a good deal of experience with IoT Edge computing, the Cognitive Service Container Instances, Azure Machine Learning and the Custom Vision service are great examples of AI on the edge.

14. How will DeepStream integration with Azure IoT edge be supported and any upcoming features or modules for IoT edge?

Great question take a look at the documentation and great demonstration video here from my Colleague Paul DeCarlo.

15. In your opinion when is it good to use Databricks and when is it good to use AzureML?

This is a really good question that deserves a more in depth follow up post. As a general rule of thumb in my experience it makes sense to use Databricks for data process and AzureML for model development and deployment. Stay tuned for a more in depth follow up post.

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About the Author

Aaron (Ari) Bornstein is an AI researcher with a passion for history, engaging with new technologies and computational medicine. As an Open Source Engineer at Microsoft’s Cloud Developer Advocacy team, he collaborates with Israeli Hi-Tech Community, to solve real world problems with game changing technologies that are then documented, open sourced, and shared with the rest of the world.