November 2018

Volume 33 Number 11

.NET Core - Publishing Options with .NET Core

[.NET Core]

Publishing Options with .NET Core

Jamie Phillips

Explore the publishing options for .NET Core applications. Two of these-- framework-dependent deployments and self-contained deployments--ship out of the box. A third still in development is called CoreRT deployments and generates native binaries from .NET Core-based code.

The Working Programmer - How To Be MEAN: Testing AngularlyColumn

[The Working Programmer]

How To Be MEAN: Testing Angularly

Ted Neward

It’s pretty clear that testing is not an optional part of modern software development anymore, so Ted Neward shows you how an Angular application should be tested.

Azure Service Bus - Web Site Background Processing with Azure Service Bus Queues

[Azure Service Bus]

Web Site Background Processing with Azure Service Bus Queues

Will Stott

In this article, Will Stott shows how to perform long-running processing in the background for an ASP.NET Core 2.1 WebApp using Azure Functions and a ServiceBus queue.

Artificially Intelligent - A Closer Look at Reinforcement LearningColumn

[Artificially Intelligent]

A Closer Look at Reinforcement Learning

Frank La

Reinforcement learning is one of the most exciting spaces in artificial intelligence. In this article, Frank La Vigne explores the Epsilon Greedy algorithm with the classic “Multi-Armed Bandit” problem, focusing on the explore-or-exploit dilemma that AI agents face.

.NET - Create Your Own Script Language with Symbolic Delegates

[.NET]

Create Your Own Script Language with Symbolic Delegates

Thomas Hansen

Tired of the complexity of modern programming? Thomas Hansen is. In this article, he presents a home-brewed scripting language for .NET called Lizzie that uses symbolic delegates--a C# design pattern based on looking up delegates from a dictionary using strings as keys.

Test Run - Introduction to the ML.NET LibraryColumn

[Test Run]

Introduction to the ML.NET Library

James McCaffrey

James McCaffrey demonstrates a logistic regression approach to binary classification in order to introduce you to the ML.NET library, which has its origins as an internal Microsoft development tool. Unlike Python-based libraries like CNTK and TensorFlow, ML.NET integrates seamlessly into .NET applications.

Machine Learning - Analyzing Olympic Diving with Sensors and Vision AI

[Machine Learning]

Analyzing Olympic Diving with Sensors and Vision AI

Kevin Ashley

This article is the second in a pair focused on the use of sensor telemetry and machine learning to improve sports training. Learn how Microsoft has partnered with the U.S. Olympic Diving Team to use sensor data, Vision AI and synced video to analyze diving mechanics.

Don't Get Me Started - For Whom the Bell TollsColumn

[Don't Get Me Started]

For Whom the Bell Tolls

David S. Platt

From Big Tobacco to defense contractors, good people must contend with the dilemma that the products they build can often be used to do bad things. David Platt is here to help us work through the rationalization.

Editor's Note - Sensors in Sports: A Dive Into Applied Machine LearningColumn

[Editor's Note]

Sensors in Sports: A Dive Into Applied Machine Learning

Michael Desmond

Back in April we published our first Sensors in Sports feature, recounting Microsoft’s work with the U.S. Olympic Ski Team to improve training using sensor telemetry and AI. Now our second article in the series look at Microsoft’s work with the U.S. Olympic Diving Team.