Tailwind Traders recent internal employee survey showed their employees are frustrated with lengthy processes for simple actions, such as booking vacation and other company benefits. They want to reduce the friction of reviewing and booking vacation so it’s a simple, easy and pleasant process for their employees. In this session you will see how Tailwind Traders applied Conversational AI best practices to simplify the vacation process for their employees. Using the Bot Framework Composer tooling you can quickly build conversation flows, incorporate intelligence services such as Q&A maker and LUIS, test and deploy your virtual assistant to the cloud and embed it where your customers and employees spend their time.
Demo 1: The first demo will go over the difference between unstructured data and structured data. We will explain why using Blob Storage was a good option in this scenario. In this demo, the use of the Azure Storage Explorer will be shown as an easy and applicable tool to utilize when dealing with different storage types. Finally, we will cover how to retrieve data from the blob and parse that data.
Demo 2: The data is retrieved from blob storage and analyzed using the Azure text analytics service, including sentiment analysis and key phrase extraction. We also show how LUIS can be very effective when working with support tickets and emails by training LUIS to understand support tickets and categorize each one.
Demo 3: Now we want to optimize Tailwind Traders' response to new customer support requests and extract insights from the data. We set up Logic Apps to send users an automated email tailored based on users' requests. Finally, we show how to use Power BI to leverage new insights to drive business decisions.

Azure Synapse is being created as a one stop solution for all your data needs. It aims to join the two large requirements of the evolving data world - relational data and big data. To fully unleash the power behind your data, you need to be able to leverage both these types of data and apply machine learning and business intelligence on top of it. Azure Synapse combines ingestion, preparation and analytical capabilities with Azure Machine Learning and PowerBI. Join me in a session to walk through what an end to end solution might look like for you in this brand new product. We will go through how Synapse enables you to prep the data, train models and generate reports without having to leave the workspace. You will leave with a better understanding of the product, it's capabilities and guiding principles on using it.

Tailwind Traders recent internal employee survey showed their employees are frustrated with lengthy processes for simple actions, such as booking vacation and other company benefits. They want to reduce the friction of reviewing and booking vacation so it’s a simple, easy and pleasant process for their employees. In this session you will see how Tailwind Traders applied Conversational AI best practices to simplify the vacation process for their employees. Using the Bot Framework Composer tooling you can quickly build conversation flows, incorporate intelligence services such as Q&A maker and LUIS, test and deploy your virtual assistant to the cloud and embed it where your customers and employees spend their time.

MLOps empowers data scientists and machine learning engineers to bring together their knowledge and skills to simplify the process of going from model development to release/deployment. This allows practitioners to automate the end to end machine Learning lifecycle to frequently update models, test new models, and continuously roll out new ML models alongside your other applications and services. We will be covering how you can get started with MLOps using GH Actions and Azure ML as building blocks.

This session will cover the very basic of Face API, and a hands on Understanding of end to end application for Face API deployed in Azure Cloud.

AI has become the most popular buzz word among tech and non-tech individuals and we talk about its applications in daily life. The applications are getting more and more complex, and classical computers are not able to handle most of the work. In this talk, I would like to demonstrate how a hybrid Quantum-Classical Machine Learning model will work and how it can benefit us in the longer run.

Learn how to use Azure custom vision to build and train your model with no lines of code. Use this model in a webapp.