At least not in the way that TensorFlow did. They provided CTK and Azure Machine Learning for cloud-based analytics, but they never seemed to take off. Microsoft didn’t enter the game thus far. Python and TensorFlow are one step ahead of others and are favorite technology combo. That is true for the machine learning as well, since today we can build our own machine learning models for real problems on home computer. This term means that technology is moving from the period where this was practiced only by the few to a place where it is no longer a novelty. First one is that the technology is crossing the chasm. There are few reasons we need to consider. Why Machine Learning?īefore we continue with the task at hand, let’s just take a moment and reflect on why is Microsoft introducing this technology now and why should we care about it. Also, now you can load modules that you have built with TensorFlow into ML.NET. If you are having ASP.NET application with the request for machine learning module, you will integrate the ML.NET one much easier. In general, there is no specific reasons to go this way except the technology stack. NET world on our own computers.Īctually, I gave a talk at local Microsoft conference – Tarabica about this technology and the main question was “Why should we use this one instead of Python and TensorFlow?”. With this tool we are able to build and test machine learning models in. NET Core 3 we got a new toy to play around. But hey, third time is the charm, so hopefully I will not have to do this again until ML.NET 2.0 🙂 Anyhow, with. Both times, guys from Microsoft decided to modify the API and make my articles obsolete. Basically, I wrote one when ML.NET was a version 0.2 and one when it was version 0.10.
In fact it made me so happy that this is the third time I write similar guide. NET Core 3, a new feature will be available – ML.NET. You can imagine my happiness when more than a year ago, Microsoft announced that as a part of. I had to solve another obstacle and learn other programming languages more fitting for the job like Python and R. One of the main reasons was the fact that I couldn’t start Visual Studio and try out these new things in the technologies I am proficient with. NET world, it was quite hard to get into machine learning right away.
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