Demystifying usage of AI and ML with Azure Server-less

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As I made my way into the city of Mumbai, I started realizing that it is actually happening, the big day you have been waiting for so anxiously is finally here.

It was an honour to deliver a session at 2019 Azure AI tour in Mumbai. I was invited as a speaker and held a 45-min session on “AI/ML with Azure Server-less”. The Conference was held at the Microsoft office, Santacruz East, Mumbai. This was my first time attending the Microsoft Azure conference. It was great fun and the conference was very well organized.

Here are a few stats from the conference; it had around 70 attendees from different states and 7 speakers delivered 7 sessions.

Event kicked off on bright note,  Noelle LaCharite, the developer experience lead for Applied AI at Microsoft covered various aspects of AI, with ease of learning and provided code base for developers. She also presented handful demos of few cognitive services.

Gandhali Samant (Sr. S/W Engineering Manager – Financial Services Cloud architect at Microsoft), presented different business case studies where Microsoft Azure AI was widely and successfully being used. Along with the informative slides presentation, she also presented few videos documented as a part of Artificial Intelligence implementation.

I had the pleasure to deliver a 45-min session and it was wonderful interacting with a lot of Azure architects, .Net Devs and Data science experts.

 Here are the quick highlights of my session:

My session started with Azure AI computer vision service, custom vision service and Azure Functions. Furthermore, I demonstrated the usage of services in Azure functions by bindings and Azure Signalr. I also spoke about code in .Net and Python.

Some of the highlights of my session are below:

  • Serverless architecture: The What & Why

The ‘What’ part included:

  • managed compute service (FaaS)
  • Leverage SaaS products

The ‘Why’ part included:

  • Reduced Ops, Focus on Business Logic, Reduced Time to Market

I further explained Solution implementation using Azure function .net and python sdk and Azure signalr.

  • Azure function

Triggers Timer, Http, Blob, Cosmos Db, Queue, Event Hub

  • Bindings

Blob and signalr

One of the most pivotal things I displayed, were the use cases for Computer Vision Service. It customises your own state-of-the-art computer vision models for your unique use case. Just upload a few labelled images and let Custom Vision Service do the hard work. With just one click, you can export trained models to be run on device or as Docker containers. The use cases included the following:

Use case 1:


When image is uploaded:

  • identify applicable tags
  • identify face, gender, age
  • suggest possible description
  • send real-time notification

Use case 2:


Predict anomaly

  • trained using scikit-learn
  • saved using pickle on Azure blob
  • solution to be available as service

My overall objective was to let know people that Serverless computing is a relatively new paradigm in server technology which will helps organizations convert large functionalities into smaller discrete on-demand functions that can be invoked and executed through automated triggers and scheduled jobs. Additonally, I enjoyed the overall event as it shared valuable & informative session on AI/Cognitive services/IoT/ Serverless & Cloud concepts.

Overall, the enthusiasm among all the attendees was commendable with utmost excitement to learn about Artificial intelligence. I thank Microsoft and Azure India for providing me with this opportunity. Let us learn and grow together!

Additionally, I would love to connect with you people on topics related to Serverless, Artificial intelligence. Please feel free to connect with me at my mail ID

You can find the detailed information about my session by clicking on

About Akshay Deshmukh:

Senior Lead Engineer – Nitor Infotech

Blogger, MVP @C Sharp Corner

Author @Dot Net Tricks

LinkedIn –

Love to use Azure ML, IoT, Microsoft Bot Framework, .Net Core, Angular

Love to code in C#, Python, Scala, TS, JS