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How to Automate IIS 7 Configuration with .NET

Are you tired of manually configuring IIS sites (adding Web sites, application pools, virtual directories and so on)? Use C# and the Microsoft.Web.Administration Namespace to simplify your life (or at least IIS configuration).

Deep Neural Networks: A Getting Started Tutorial

Deep Neural Networks are the more computationally powerful cousins to regular neural networks. Learn exactly what DNNs are and why they are the hottest topic in machine learning research.

Implementing Binary JSON in ASP.NET Web API 2.1

Visual Studio 2013 came with a new version of Web API. The Web API 2.1 update includes a host of new features, including support for Binary JSON. Learn how to leverage BSON by building a Web API 2.1 service.

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.

Using OAuth, Twitter and Async To Display Data

Connect to Twitter from a mobile application using OAuth with the Xamarin.Auth library, along with Joe Mayo's LINQ To Twitter library.

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.

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.

Using Portable Class Libraries in iOS and Android Apps

Portable Class Libraries create a single DLL that can be used across platforms, making code sharing easier. Learn how to use them by building a weather app with a portable core.

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.

Creating Custom ASP.NET MVC Filters

ASP.NET MVC filters can be defined once and used in multiple places. Because ASP.NET MVC also provides the ability to create custom filters, it's good practice to learn how to make them and use them in your own projects.

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.

Tracking Your Windows Phone App Analytics with VSO's Application Insights

Nick Randolph walks through adding analytics to your Windows Phone application using Application Insights for Visual Studio Online.

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