Machine Learning adoption for .Net Applications
New products and applications are benefiting with new digital trend of artificial intelligence (AI) and machine learning (ML). They are taking advantage of many available frameworks such as TensorFlow, PyTorch, Keras, MXNet and DL4J. Prominent frameworks have Python as their programming language and so it becomes preferred language while developing new product.
In such scenario, new product development benefits, however, there exists large number of already development products which can not take direct advantage of Machine Learning. These products already have large data sets from their real life use. They might have built some business Intelligence capabilities as well.
This data can be used now to create Machine Learning models & train those effectively. Machine Learning .NET (ML.NET) is an open source offering from Microsoft. It leverage your existing development capabilities such as C# as primary programming language and you can Machine Leaning capabilities in your product very quickly. You can identify area in your product, which can be transformed with Machine Learning adoption. Determine if you can use existing models or build your own model. Identify data from your product, which can be used to train your model. Evaluate you model with scenarios and integrate & pin the model. If you are using predefined models and have readily available training dataset, you can literally add Machine Learning capability to your product in no time.