For the uninitiated, ML.NET is the newest entry from Microsoft providing new machine learning framework that promises high-end APIs. This has been designed to make model training and predictions easy, along with seamless integration of .Net language features.
Over the years, .Net framework has aided the programmers learn completely efficient dynamics of machine learning and seed the capability of artificial intelligence into programming.
ML.NET was first announced in 2018 and since then the active community has provided its valuable feedback and inputs to the existing. The inputs can come from anyone, be it a freelance ASP.NET developer or an ASP.NET web development company. These delightful and worthy insights has made what ML.NET framework is today.
This has paved a way for the .Net developers to create and manage models for distinct tasks and made them available to .NET applications through high-level APIs for model training and prediction requirements.
When ML.NET was released initially, it included only two basic machine learning tasks:
Classification- Used for categorizing the data including spam versus legitimate email, or the likes of sentiment analysis.
Regression- Used to perform prognosis on various numerical data viz pricing trends. The sample applications which are included with the GitHub repo for the project provide examples.
The most recent release of ML.NET 0.4 has an added support for tasks such as Natural Language Processing or NLP. Microsoft wants ML.NET to support a wide range of tasks in the upcoming future.
It is safe to believe that while some of the tasks will be parched directly into the framework, and for the other tasks, ML.NET’s high-level APIs will be utilized in order to power the existing frameworks such as Google’s TensorFlow or Microsoft CNTK-Cognitive Toolkit.
Ahead of the Version 1.0 release, Microsoft may have a trick or two up its sleeve. They plan to decommission the current “pipeline” API, and replace it with another API which is designed to be easier to use.
The focus of Microsoft is to make ML.NET cross-platform by design. .NET currently supports the Windows, Linux, and MacOS incarnations of .Net Core 2. Similarly, ML.NET is intended to leverage all the features available in the .NET family of languages.
To give you an example, a particular change in Version 0.4 now better supports F# records, including some of the analogous features in C#.
Conclusion
The demand to hire ASP.NET developers today is surging. With the market potential of .NET development experiencing a boom, entrepreneurs and organizations feel a need to inculcate .NET development for their needs. The first point of contact for them will be an ASP.NET web development company, hence it becomes imperative for companies to improve their existing dynamics and move to the next level.
