Jeśli interesujesz się uczeniem maszynowym i zastanawiasz się jak wykorzystać jego możliwości w .NET, warto zapoznać się z rozwiązaniem ONNX.
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ml.net
Bri October 4th, 2021 ML.NET is an open-source, cross-platform machine learning framework for .NET developers that enables integration of custom machine learning into .NET apps. In this post, we’ll cover the following items:Model Builder updatesProgress on addressing ML.NET pain pointsGet started and resourcesModel Builder updatesNotebook Editor in Visual Studio Interactive Notebooks are used extensively in data science and machine learning. They are great for data exploration and preparation, experi...
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W tym odcinku odpowiedzi na pytania: 💠 Czy developer C# potrzebuje Machine Learning? 💠 Czym jest uczenie maszynowe? 💠 Jaki problem rozwiązuje programista i ML Engineer (Data Scientist)? 💠 Jak wygląda proces ML? 💠 Czy Data Science to nadal egzotyczny zawód dla naukowców? 💠 Czym jest ML, a czym AI? 💠 Czy ML to tylko Python? 💠 Dlaczego Python jest tak popularny w Data Science? 💠 ML.NET - co jeśli cały stack technologiczny mam w .NET?
More and more has been saying recently about the concept of no code. It is a platform for building applications without coding. You can create software and configure everything using just the mouse, a perfect way for non-technical people. ML.NET Model Builder can be described as a small seed of this solution. In this article, I want to show you how easily can you create a prediction model for your recommendation application with a few clicks.
Źródło:
bush-dev.com
Dziel się z innymi:
Transfer Learning is a popular tool in the field of Deep Learning. It is used to reuse a previously created model for a new problem. Thanks to that you can train neural networks with little data, which significantly saves time and memory resources required. This type of algorithm is also available in the ML.NET library. I want to show you its use on the example of Image Classification using a pre-trained TensorFlow model.
Źródło:
bush-dev.com
Dziel się z innymi:
I wrote there about what this type of regression is and showed how it can be implemented in F # using the ML.NET library.
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