ML applications for businesses in dotnet
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.NET has been one of the most popular programming technologies for years, and it’s still one today according to Stack Overflow’s Survey.  

Many important applications, from webs like GoDaddy to game-development platforms like Unity, are powered by .NET. And even though Python remains the first choice for Machine Learning (ML) and other AI projects, C# is making its way into GitHub’s top list on the topic.  

So what makes it such a frequent choice for big companies implementing ML?  

Let’s delve into some of the main features before reviewing possible applications powered by this technology and its benefits.  

What is .NET?  

According to Microsoft’s website, .NET is a cross-platform development environment. But what does that mean, exactly?  

Well, .NET is basically a set of tools for programming and building any kind of apps and functionalities. It supports several multi-purpose programming languages, being C# and VB.NET the most important of them.   

So, whenever we talk about .NET, we are talking about a package of tools powered by Microsoft, oriented to provide software programming solutions. All of them are available by installing the .NET SDK (Software Development Kit), which includes:  

  • C#, F#, and VB compilers 
  • Build utilities (MSBuild, MSTest, etc.) 
  • Runtimes 
  • Many built-in libraries  
  • A package manager (NuGet) 
  • The command line interface (dotnet CLI)  

Therefore, when people speak of .NET developers, they often mean experienced C# programmers -which is the most common of the languages supported by .NET- who know the .NET framework well and are able to build back-end software solutions for enterprises. 

Why is it so popular? 

.NET relies on Microsoft’s support and vision, which simplifies and assures many of the processes attached to building complex, sustainable applications. For companies in the software industry, the .NET framework offers a series of essential solutions, such as:  

  • Stability across time 
  • A complete, objected-oriented framework for app development 
  • It’s cross-platform running on macOS, Linux, Windows, iOS, and Android 
  • Scalability 
  • Large ecosystem 

This condition differentiates .NET framework from other open-source technologies such as Python or Java, providing a much safer and more stable context for upgrades and long-term software design. Having Microsoft as a supporter, its solutions are already provided, tested, and integrated without forcing companies to rely on self-made research and development. 

Machine Learning: Implementation in .NET 

Machine Learning is one of the hottest topics in computer science’s present time. The availability of large datasets related to the use of the internet is allowing this discipline to impressively grow and develop business-oriented solutions for several industries. As programs learn to improve performance when provided with more data points, several new projects became not only possible but seemly easy to achieve if counting with the right technology and professionals

Considering different business needs, some of the most interesting applications are:  

1) Sentiment Analysis 

This practice consists in taking natural language texts, analyzing them, and classifying them according to their opinions or feelings. This way, it allows a program to determine whether a text contains positive, neutral, or negative connotations.  

For businesses, sentiment analysis is a great tool for knowing and understanding both their customers and employees. When having hundreds or thousands of them, there isn’t always time to analyze reviews and comments one by one, so such programs are useful for discovering trends and reactions to different products and decisions.  

ML applications for businesses in dotnet

2) Product Recommendation 

Another application of ML (Machine Learning) has to do with customization. In this sense, the possibility of tracking users’ preferences and previous searches can be a powerful tool for recommending accurate future purchases. Implementing ML allows your programs to optimize recommendations and find the perfect product for each customer.  

3) Customer Segmentation 

Customer segmentation allows businesses to better understand their customers. Knowing the distinctions between customer cohorts makes it easier to make strategic decisions about product development and marketing. 

Machine learning methodologies are an excellent resource for analyzing customer data and uncovering insights and patterns. Artificially intelligent models are powerful decision-making tools, as they are able to precisely identify customer segments, which is much more difficult to do manually or with traditional analytical methods. 

4) Fraud Detection 

Machine learning in fraud detection is a collection of artificial intelligence (AI) algorithms that have been trained with historical data to suggest risk rules. The rules can then be used to block or allow specific user actions such as suspicious logins, identity theft, or fraudulent transactions. 

5) Sales Forecasting/ Spike Detection 

Forecasting sales is a common and essential application of machine learning (ML). Forecasted sales can be used to find benchmarks and figure out the incremental impacts of new initiatives, plan resources in response to expected demand, and project future budgets. 

Another profitable use of ML for sales is spike detection, which allows tracing change points in product sales through time. This way, businesses leverage ML for making specific, fast, sales-oriented decision-making.  

.NET’s Solution for Machine Learning 

For this kind of project, Microsoft created ML.NET, a specially designed framework for training, building, and shipping custom Machine Learning models for a variety of scenarios. Its set of tools and features makes the process of powering applications with ML as easy as it can be. 

Besides, being a Microsoft-powered programming environment, .NET works directly with Azure Services, enabling cloud deployment without needing to manage infrastructure. 

Leveraging .NET, Boosting Business Processes 

.NET is one of the best options among development environments for companies’ software projects. One of the most significant aspects is its constant renovation through cutting-edge technologies, such as AI, ML, and Cloud services.  

If you’re looking for top-level engineers to join your team and leverage your .NET-powered digital ecosystem, don’t hesitate to contact us. We are here to help companies grow their businesses through high-tech software development. 

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