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.
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.
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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