C#


Understanding the Android Resource System

Learn how to leverage the powerful resource system of Android to support a variety of Android devices and languages.

Visual Studio 2013 Update 3 Gets its First CTP

The Update comes fewer than two weeks after the official release of Update 2 at TechEd North America.

How To Refactor for Dependency Injection, Part 1: Cleaning Up

Take control of your application's behavior and move toward dependency injection by refactoring your existing code.

Neural Network Dropout Training

Dropout training is a relatively new algorithm which appears to be highly effective for improving the quality of neural network predictions. It's not yet widely implemented in neural network API libraries. Learn how to use dropout training if it's available in an existing system, or add dropout training to systems where it's not yet available.

Using Knockout Custom Binding Handlers

Knockout custom binding handlers can help simplify integration with third-party JavaScript libraries. Here's how.

Neural Network Cross Entropy Error

To train a neural network you need some measure of error between computed outputs and the desired target outputs of the training data. The most common measure of error is called mean squared error. However, there are some research results that suggest using a different measure, called cross entropy error, is sometimes preferable to using mean squared error.

Telerik Makes Kendo UI Available as Open Source Platform

Kendo UI Core includes the entire mobile framework.

Microsoft Makes 'Roslyn' Compiler Open Source

Also announced was a new interop organization called The .NET Foundation.

Microsoft Promises C++ Power, C# Dev Efficiency With .NET Native

The developer preview was released yesterday.

Microsoft Takes Cross-Platform Development to Another Level

Release Candidate 2 of Visual Studio 2013 also announced.

Neural Network How-To: Code an Evolutionary Optimization Solution

Evolutionary optimization can be used to train a neural network. A virtual chromosome holds the neural network's weights and bias values, and the error term is the average of all errors between the network's computed outputs and the training data target outputs. Learn how to code the solution.

ASP.NET MVC Extensibility with MEF

How to use MEF to add validation rule components to an ASP.NET MVC Web application.

Regular Expressions, Part 3: Business Intelligence Uses

You can do a lot more with regular expressions than you think. In this tutorial, you'll use it to convert a movie list into a CSV file for use in Excel.

.NET Development Available on Red Hat Open Source Platform

The technology was developed by a company founded by two ex-Microsoft executives.

.NET Framework Reference Source Updated Via 'Roslyn'

Developers can search for incompatibilities between their own code and .NET more easily than ever.

TypeScript & Visual Studio 2013: Coming of Age

Visual Studio 2013, with the latest version of TypeScript, gives you the same kind of support you've come to expect when writing code in C# and Visual Basic.

Out To Lunch

Why user requests shouldn't always be granted.

Learning to Use Genetic Algorithms and Evolutionary Optimization

Evolutionary optimization (EO) is a type of genetic algorithm that can help minimize the error between computed output values and training data target output values. Use this demo program to learn to the method.

Visual Studio 2013 Add-In Allows Code Searching Across Web

With Bing Code Search, Visual Studio developers get context-aware search capabilities from within IntelliSense.

How To Standardize Data for Neural Networks

Understanding data encoding and normalization is an absolutely essential skill when working with neural networks. James McCaffrey walks you through what you need to know to get started.

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