Active Solution Play

Durable Functions, Micro Services, Singletons & Orchestration

In this demo I’ll create a globally available web application hosted in three azure regions using Azure Front Door.

In this webcast I’ll demonstrate how the Cosmos DB autoscale functionality can be utilized to dynamically adjust the provisioned resource capacity to process varying loads from Twitter data streams.

In this webcast I’ll run through the core functionality of the Azure Cognitive Services Computer Vision service.

In this webcast I’ll explore how the Game of Thrones world can be modeled and traversed (queried) using the Graph model in Azure Cosmos DB. I’ll also show how friends recommendations can be made for various Game of Thrones characters.

This session contains a large number of executions, but hopefully no major spoilers.

In this webcast I’ll explore the Azure Cognitive Services Computer Vision Service using the C# Client SDK. I will cover the authentication, image description, tags and object detection, and round off with logo and celebrity detection.

In the webcast we’ll see if the Azure Cognitive Services Content Moderator service can handle Quentin Tarantino.

In this webcast I’ll explore the Azure Cognitive Services Computer Vision Service using the Python SDK.

In the first session in this 6 episode series, we will introduce the basics of Azure´s AI & Machine Learning, and demonstrate what the platform is capable of. This session will focus on getting you to know the concepts, terminology and tools to get started with AI & ML on the Azure platform.

This session will highlight the platform as a service (PaaS) services in Microsoft Azure that can be leveraged to form the foundations of a cloud-based event driven architecture. We will cover the capabilities of the messaging and eventing technologies in detail and provide guidelines on selecting the appropriate service for a given scenario. We will also demonstrate how these services can be integrated with other Azure services to develop a cloud-native, serverless event driven application.

In this session Alan will introduce the concept of serverless architectures and discuss how they can be used to create manageable, cost effective and highly scalable cloud-based applications. He will then cover the core platform as a service (PaaS) services in Microsoft Azure that enable serverless to be created and demonstrate their usage. The hosting costs for applications created with serverless architectures will be covered along with tips and guidelines for developers.

For many developers getting to grips with data science, artificial intelligence and machine learning can seem challenging with quite a steep learning curve. Whilst many of the advanced concepts do require a significant amount of learning, it is possible to make a start on this journey by getting to grips with the basic concepts of machine learning and understanding how algorithms can be trained using a suitable data set. Microsoft Azure provides a range of services and technologies that can be leveraged by people new to machine learning that will increase productivity and help to provide a gentler learning curve.

Microsoft uses reinforcement learning in many ways to improve our products and services. AI and machine learning can help accelerate game development by providing more realistic worlds and challenges as well as support automation and live operations.

At Game Stack Live, Microsoft Research announced Project Paidia, a research effort aimed at exploring new opportunities created with AI based reinforcement learning in gaming. During this session, attendees will be able to get started with Reinforcement Learning for gaming with the use of Azure Machine Learning.

The Azure Custom Vision service enables users to easily train convolutional neural networks (CNNs) for classification and object detection. These trained models can then be leveraged by custom vision applications as could-hosted services. The custom vision service also supports the exporting of trained models, allowing them to be used on-premises and on mobile devices for near-real time vision applications.

In this developer focused session Alan will start with the basics of neural networks and explain how they can be trained to clarify images. He will them move on to more complex convolutional neural networks (CNNs) and explain the details of object detection.

The use of the Azure Custom Vision service to train CNNs will be demonstrated using both classification and object detection examples with tips on techniques for training the networks effectively. The use of these trained networks will be demonstrated by calling the cloud-hosted services, as well as using and exported network model in an on-premises application for real-time object detection using a video stream.