Machine learning is a popular application of artificial intelligence. It provides a system that can automatically learn and improve using past experiences or interactions.
It is applied to web services and applications for extra functionality, but you can also use machine learning in .NET development using the machine learning library known as ML.NET.
But how to use it? What are the benefits of using machine learning in .NET?
Don’t worry. We’ve got you covered.
We have compiled the nitty-gritty elements of machine learning in the .NET framework that can help you make informed business decisions about your web applications and software.
So, without further ado, let’s get the learning started.
Why Are .NET Development Solutions Still Relevant in 2024?
Microsoft developed the .NET framework as a cross-platform, open-source software tool for application development.
It is a full-stack framework that can help you build websites, desktop and web applications, games, and more. Still, after 20 years since its release, it’s highly popular in the professional development ecosystem because of its features and flexibility.
The biggest companies in the ecosystem use it for their web applications, like Dell, JP Morgan Chase, Samsung, and Cisco. .NET is also used to build different web resources by companies like StackOverflow, GoDaddy, and Intel.
There have been multiple advancements in the open-source ecosystem, and it has been made compatible for accessing the machine learning benefits.
Machine learning applications are based on Python. But the language can hinder the production process in the .NET environment. The situation can worsen when C# is used in the .NET project’s development.
To bypass the problem, Microsoft introduced .NET’s machine learning library called ML.NET helped to make the use of machine learning in .NET.
What Essentially Is Machine Learning In .NET?
Machine learning in .NET can be used by accessing Microsoft’s cross-platform, open-source machine learning framework for all the .NET developers.
The ML.NET is the face of machine learning’s presence in the .NET framework and can be used on operating systems like macOS, Linux, and Windows.
A .NET developer can create or develop different MC models using F# or C# without switching from the .NET framework with the help of ML.NET.
The ML.NET framework can enable the .NET developers to incorporate artificial intelligence into applications by developing custom ML-trained models for scenarios like sales forecasts, sentiment analysis, future price predictions, and customer satisfaction.
The ability of ML.NET to create and train ML models paves the way for multiple applications and use cases in the .NET framework that can help you achieve your desired business outcomes.
Scope of Machine Learning In .NET
The scope of machine learning in .NET is great because of the ML.NET libraries. It enables the developers to use the .NET skills to integrate machine learning into different .NET applications.
Freedom for .NET developers
The developers can work in C# and skip the part of learning new programming languages like R or Python to use machine learning to maximum effect within the .NET ecosystem.
You can ask the developers to integrate custom machine learning into your web applications. .NET developers can easily train, build, and deploy different custom machine learning models on the computer with no prior machine learning experience.
Interoperability with data scientists and Python
The developers can use ML.NET to access Python bindings called NumbusML. You can assign the task to your data scientist (if they are skilled in Python) to create ML.NET models with NimbusML.
These machine learning models can be used in end-user .NET applications that can help you unlock your desired outcomes.
Python binding NumbusML is interoperable with scikit-learn transforms and estimators and with other libraries in Python like Pandas and NumPy.
Python developers and data scientists can find it easier to create and train ML.NET models that can run on .NET applications.
Proven and trusted at scale
The ML.NET was announced in 2018, but it has evolved into a prominent machine learning framework that adds features in different Microsoft products like Bing Suggested Search, Microsoft Defender ATP, Excel Chart Recommendations, PowerPoint Design Ideas, and other Azure services.
Multiple other companies have also used ML.NET to add different machine learning scenarios to multiple .NET apps, proving that the framework is widely accepted worldwide.
The technology is proven and has a great potential to deliver the best results in the .NET framework ecosystem.
Workflow Process of Machine Learning in .NET
The use of machine learning in .NET enables the developers to integrate and build different machine learning models in the .NET ecosystem, and these models follow a workflow process as follows:
- Data is collected and loaded as an object.
- The pipeline is built, and data is combined with the pipeline
- The machine learning algorithm is applied to the data synced with the pipeline to extract features.
- The model is trained and then evaluated for more improvement.
- Predictions are made based on the evaluation.
The workflow is blazing fast with ML.NET and delivers excellent machine learning applications in the .NET framework to ensure that your web apps deliver the best results.
ML.NET outperformed the SciKit-Learn and H20 frameworks, making it more reliable and faster on large and small data sets.
It can integrate with different machine learning libraries such as ONNX, Infer.NET, and Tensor Flow, which increases the horizon of the use of machine learning in the .NET framework.
Benefits of Machine Learning in .NET
There are different benefits of machine learning in the .NET framework. Your developers don’t need to be experts in artificial intelligence or machine learning to use ML.NET, making it seamless for the development team to test and build models.
It comes in a pre-packaged form with different ready-to-deploy models. Your developers can load the data, and ML.NET handles the rest of the process with finesse.
Using a machine learning ecosystem in the .NET framework makes the production process easier for your enterprise-application developers because of the overlap in the coding language integration.
Machine learning provides an extra edge to the .NET web apps and software as you can use different machine learning applications to train the model and improve the results for using the applications.
You can use different virtualization tools like PowerBI, and Microsoft Azure, among others, with the help of ML.NET, which can enhance the visual impact of your applications.
The Future of Machine Learning in .NET Development
You might think about the future of machine learning and the .NET framework together. In the present scenario, the future of the combined power of ML and .NET looks brighter than ever.
With the world switching towards a powerful and effective AI-era, .NET web apps and software need an extra edge provided by machine learning that can reach the next level.
The use of machine learning in .NET web apps and software enhances the capabilities of the applications and adds a modern layer of artificial intelligence to them.
Both the technologies will grow side by side and can be used together to achieve better results and outcomes.
With continuous updates and tweaks by Microsoft in the .NET ecosystem, the time is near when ML.NET will become the industry standard for different enterprise-application ML integrations.
ML.NET will expand in the future and provide the .NET developers with more chances to contribute to the artificial intelligence and machine learning ecosystem.
As an early adopter of the technology shift, you can explore the benefits of machine learning in .NET apps and software and stand out from your competitors.
How Can Integrative Systems Help With .NET Development Solutions?
The increased dependency on machine learning and the .NET framework must be tackled professionally if your organization needs to futureproof.
You need to integrate modern machine learning in your .NET-based web apps and software that can help you get an extra edge in the industry.
But you need a professional team of .NET developers that can help you provide excellent .NET development solutions that enable the integration of machine learning into the existing .NET framework.
Hiring and building your in-house team can be tiring and costly, but you can choose to outsource your requirements to a professional DOT NET development company.
We at Integrative Systems can help you use machine learning in .NET apps and software to modernize your business ecosystem and help you achieve your desired business outcomes with finesse.
Our 20 years of experience handling .NET projects enables us to use the framework to its maximum potential. We have adapted to the new updates and features of the .NET world and are fully equipped with the knowledge and experience to handle your unique requirements.
We can solve the complexities of your requirements and deliver you customized and optimized web apps and software .NET development solutions.
Discuss your project requirements and bypass your machine learning and .NET development hurdles.
Please get in touch at [email protected].
