I was checking out the TensofFlow samples available in the repo but looks like in all of them (Image Classification, Object Detection) the samples are just running/scoring pre-trained TensorFlow models such as Inception v3:

https://github.com/SciSharp/TensorFlow.NET/blob/master/test/TensorFlowNET.Examples/ImageProcess/ImageRecognitionInception.cs

https://github.com/SciSharp/TensorFlow.NET/blob/master/test/TensorFlowNET.Examples/ImageProcess/InceptionArchGoogLeNet.cs

https://github.com/SciSharp/TensorFlow.NET/blob/master/test/TensorFlowNET.Examples/ImageProcess/ObjectDetection.cs

Do you support more advanced scenarios such as:

Do you have (is it possible with TensorFlow.NET?) any example on how to do 'Transfer Learning' with TensorFlow.NET such as training with new images on the final layer and even on multiple layers (and ultimately possibility for the full network) of the TF network?

The following is a basic 'Transfer Learning' sample using Keras/Python.

https://github.com/dotnet-architecture/eShopOnContainersAI/blob/dev/workbench/keras_training.py

I mean something comparable to that but using TensorFlow.NET.

Thanks! :)