I am trying to create a visualisation for how transfer learning (feature extraction in particular) works with MobileNet.
ml5.js library, you can extract a part of the pre-trained model (the features). Those features allow you to 'retrain' or 'reuse' the model for a new custom task (transfer learning). Then, we can map the features to our own set of labels.
I found a good explanation here. I tried to visualise the process according to the just-mentioned video.
However, this figure doesn't show anything about the retraining. Here, it looks like we're not doing any training at all and just mapping the whole thing to our custom labels.
What could be a good way to visualise the feature extraction process with MobileNet?
Here is the ml5 featureExtraction documentation: