Volume 32 Number 11
November 2017 Code Downloads
|Cognitive Services - From Text to Targeted Sentiment Analysis with Cognitive Services
Learn how to use the Text Analytics and Linguistic Analysis APIs of the Microsoft Cognitive Services to analyze text, such as customer reviews, to find out how your customers feel about your products and services.
|DevOps - Continuous Data Migration Using Visual Studio and TFS
Continuous integration is a core, accepted practice in modern application development. So why shouldn’t data be treated the same way? Learn how to set up continuous SQL data migration using Visual Studio and Team Foundation Service on a SQL project with an established production data model.
|Machine Learning - Azure Machine Learning Time Series Analysis for Anomaly Detection
Anomaly detection is one of the most important features of IoT solutions that collect and analyze sensor data over time. Dawid Borycki extends his RemoteCamera UWP app to show you how to use Azure Machine Learning Time-Series Anomaly Detection to identify anomalous sensor readings.
|Security - Secure Data and Apps from Unauthorized Disclosure and Use
Data is only as secure as the apps that process it, and even production apps can expose their data to a debugger. Joe Sewell explains how tooling included with Visual Studio can make your .NET apps detect, report and respond to unauthorized debugging and other runtime attacks.
|Test Run - Kernel Logistic Regression Using C#
Kernel logistic regression (KLR) is a machine learning technique that can be used to make binary predictions. James McCaffrey explains how it works and presents a demo program to illustrate.