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Infusing Artificial Intelligence and Machine Learning into .NET Applications

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Infusing Artificial Intelligence and Machine Learning into .NET Applications

Here is a discussion about the advantages of using .NET as your primary programming platform for developing AI/ML applications.

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ASP.NET is a great framework that covered numerous programming languages in one single roof. It has become a popular choice for developing business oriented apps for many years.

Important Benefits of ASP.NET Over Other Development Models

1. .NET drastically minimizes the amount of code needed for building big apps.

2. Offers better performance by taking advantage of in-time compilation, early binding, native optimization, and caching service out-of-the-box.

3. Apps are secure and safe with in-built Windows authentication and per-app configuration.

4. Offers simplicity since it makes it easy to do common tasks, from simple submission of form and client authentication to site configuration and deployment.

5. The framework is complemented by a rich designer and toolbox in the Visual Studio integrated development environment. Drag-and-drop server controls, and automatic deployment are only a few of the features that the powerful tool provides.

6. HTML and source code are together, thus ASP.NET pages are easy to maintain and to write. Also, source code is executed on a server, providing a lot of flexibility and power to web pages.

7. It’s purely server-side technology, thus ASP.NET code executes on a server before it’s being sent to a browser.

8. All processes are monitored and manage closely by the ASP.NET runtime, so if the process is dead, a new process could be made in its place, helping to keep the app available constantly to handle requests.

9. ASP.NET makes for easy deployment. No need to register components since configuration is in-built.

10. Being language independent, it enables choosing the language that applies best to the app or partition the app across numerous languages.

ASP.NET Development Services

An ASP.NET development company Melbourne is a Microsoft Gold Certified Partner and works in various .NET technologies. With hundreds of thousands of project implementations and profound industry experience to implement solutions for various verticals. Service providers in Australia could be a trusted partner for .NET solutions with AI integration. Custom development with the use of the technologies of Microsoft helps tailor an app as per client budget and requirement.

Developing Artificial Intelligence wdith .NET

Recently, Microsoft released a couple of relevant AI services.

Microsoft Cognitive Services

These are APIs that allow tapping into an ever-growing collection of powerful artificial intelligence algorithms, which are developed by experts in the fields of computer speech, vision, knowledge extraction, and natural language processing and web search.

Bot Framework

Is an extremely useful framework for building and connecting intelligent bots to naturally interact with users wherever they may be, from Slack, Facebook, Telegram, Skype and other popular services.

Infuse Machine Learning and Artificial Intelligence in .NET Applications

Already, NET is equipped with everything one needs for building smarter applications, through infusing AI and machine learning for on-device and cloud scenarios. One could use the pre-built models with Core ML for Xamarin, Cognitive Services or generate and consume own models built with Azure Machine Learning, deep learning libraries such as Tensorflow, CNTK and Accord.NET.

Cognitive .NET Development Services

Add intelligent features easily to .NET applications, like sentiment and emotion detection, language understanding, vision and speech recognition, intelligent search and knowledge.

Azure Machine Learning

Azure machine learning is a completely-managed cloud service. It enables easy building, deploying and sharing predictive analytics solutions.

The Key Feature of the New ASP.NET Core MVC

The new ASP.NET Core not only equips a developer with greater flexibility, it also allows one to have a competitive edge with high-end web applications. Some key features are the following:

1. Added flexibility as an open source. Being open source, it empowers a developer to maintain modularity across the development environment for code simplification. Furthermore, it boosts flexibility of adding framework libraries and components as required for application development.

2. Cross-platform capability. ASP.NET core could be run beyond platforms such as Linux, Windows, Mac and others. Visual Studio Code is a Visual Studio component, a development tool for ASP.NET, which allows the development of apps in Linux and Mac operating systems. .NET services in a development company leverage the platform independency feature of ASP.NET Core to develop one application, which could be run on many platforms.

3. Supports hosting independence. In the development, the applications could run on web servers other than the Internet Information Services. This is because since ASP.NET Core supports cross-platform, it could not keep the application only dependent on IIS.

4. Improved cloud deployment support. Cloud deployment support is enhanced due to the modular architecture of the framework. The flexible environment and extend modularity provided by ASP.NET Core, enables building applications, which are ready to be deployed on the cloud.


For a Windows developer, using .NET is something done without thinking. Truly, a big majority of Windows business apps written in more than a decade use managed code, most of written in C#. One real advantage of writing and deploying machine learning code in .NET is one could get everything from one source. If one could write and then deploy in a single language stack, there’s great opportunity for speed and efficiency to market.


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Topics:
artificial intelligence ,machine learning ,.net ,programming platform ,ai

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