Volume 31 Number 11
November 2016 Code Downloads
|Azure IoT Hub - Capture and Analyze Brain Waves with Azure IoT Hub
Ben Perkins uses the Emotiv Insight headset to capture brain activity and load it on to the Azure IoT Hub for machine language analysis via Stream Analytics. Welcome to the future.
|Bot Framework - Solving Business Problems with the Microsoft Bot Framework
Organizations deal with a variety of applications that must work together to solve business problems. This article describes a scenario that illustrates this challenge, and shows how Microsoft Flow, Azure Search, and the Microsoft Bot Framework can mitigate the effort involved in meeting this challenge.
|Cognitive Services - Seeing the World with Xamarin and Microsoft Computer Vision APIs
Learn how the Microsoft Computer Vision API allows images to be described and analyzed using natural, human-readable, language. You can upload a picture to the Computer Vision service or point to an image URL, and expect a fully natural description back, without the need to construct and format descriptions on your own.
|Data Points - CQRS and EF Data Models
Command Query Responsibility Segregation (CQRS) is a pattern that has a lot of benefits—and some drawbacks—when you’re defining data models with Entity Framework. Julie Lerman explains why it’s worth considering.
|Modern Apps - Add Facial Recognition Features to Your App
Cognitive Services provides a rich feature set around computer vision, facial detection, and recognition. But did you know that the Universal Windows Platform (UWP) provides built- in face detection? This article will explore how to implement face detection in UWP apps.
|Test Run - Solving Sudoku Using Combinatorial Evolution
James McCaffrey explains how write a program to solve difficult Sudoku problems, using a technique he calls combinatorial evolution, a set of general guidelines that can be used to design a concrete algorithm to solve a specific optimization problem.