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Machine Learning, Big Data and Artificial Intelligence in ASP.NET

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ASP.NET: Machine Learning, Big Data and Artificial Intelligence in ASP.NET
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The best thing about frameworks is that they provide a common platform for many different programming languages. Same goes for Microsoft’s .NET framework, which is a collection of technical support that empowers both businesses as well as individual users.

Covering various programming languages on one platform, the ASP.NET framework makes for an amazing choice as compared to other development models for developing artificial intelligence and machine learning applications.

Before on moving to our main topic, let’s look at the basic terminology of Machine Learning, Artificial Intelligence, and Big Data.


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Artificial intelligence is a vast subject and cannot be explained in a single line. But precisely, any technique, code or algorithm that enables machines to develop is artificial intelligence.

Whereas machine learning is about making predictions using machine learning algorithms. The algorithm searches for patterns within the value tables.

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Big data is something that is used to show huge volume of data present in both structured and non-structured format. But it is not the amount of data that is far important. It is what any business organizations do with the data that matters.

How does Data Science relate to AI, Machine Learning and Deep Learning?

Data Science is an interesting field that has skills used in various fields such as statistics, machine learning, visualizations etc. Data Science is used at a large scale to manage, analyze and manipulate the data.

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Additionally, it helps in finding the meaning and accurate information from the chunk of data. It allows improved decision making and is a key in business science, and technology.

How all three technologies are infused in ASP.NET Framework?

One of the key advantages of the .NET framework is it reduces the amount of code required for creating big apps. It also offers a finer performance by improving early binding, in-time compilation, and native optimization.

Data engineers prefer Python and R as the popular languages for data processing. Although, they are not always the languages that the rest of an application is built on.

This is why you need to figure out a method that will deploy the machine learning models which are written either in Python or R for an environment orienting around a language such as .NET.

How to Develop Artificial Intelligence with .NET

1. Microsoft Cognitive Services

There are APIs that allow tapping into an ever-growing collection of most powerful cum intelligent algorithms of artificial intelligence that are developed by industry experts in the fields of computers speech, vision, knowledge extraction, and web search.

2. Bot Framework

This is an extremely important framework for building and connecting intelligent bots to naturally interact with users wherever they may be, from Facebook, Telegram and other popular messaging services.

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The Process of infusing Machine Learning and Artificial Intelligence in .NET Applications:

Already, .NET is loaded with everything one needs for building smarter applications, through infusing AI and machine learning for on-device and cloud scenarios.

Anyone developer is eligible to use the pre-built core models or Cognitive Services or even can generate and consume own models built with Azure Machine Learning and deep learning libraries.

Cognitive .NET Development Services

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

Azure Machine Learning

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

Key features of ASP .NET Framework:

The new ASP .NET core not only offers the programmer a suitable environment with flexibility, additionally it allows to have competitive edge with high-end web applications.

  • Added flexibility as an open source
  • Cross-platform capability
  • Supports hosting independence
  • Improved cloud deployment support

Here are some main advantages of using .NET platform which makes .NET languages the ideal choice for configuring machine learning and artificial intelligence:

  1. Although it is an open source, the new ASP .NET Core permits developers to maintain modularity across the development environment for code simplification. It also improves flexibility of introducing framework libraries as well as components whenever required for app development.
  2. It can run platforms other than Mac, Windows, Linux etc. Visual Studio Code is a developers tools for Asp.Net and facilitates the development of apps in Mac as well as Linux operating systems.
  3. And special thanks to cognitive .NET development services, programmers also gain the ability to add easily add smart features such as language understanding, sentiment and emotion detection to their .NET applications.
  4. The applications of .NET are much easy to maintain and develop and developers love to work on this language.
  5. By using the ASP .NET, all the processes runtime are managed and monitored closely, so if the existing process is not running, a new process could be replaced in its place, which supports in keeping the application available to handle requests.

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Paschal Okafor is NaijaTechGuide Team Lead. The article Machine Learning, Big Data and Artificial Intelligence in ASP.NET was written by NaijaTechGuide Team. The article was last modified: February 21st, 2019

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