In this tutorial we are going to go through all the steps required to visualize the predictions on your data in VR. We are going to use Fast.ai (that sits on Pytorch) in a jupyter notebook. The data needed for the visualization will be sent with HTTP requests in python, in this tutorial you will learn to use that too. After this tutorial you are going to be able to get visual feedback on the learning process of your neural network. We aren't going to go through how to build or train your model. We are focusing solely on the learning model's output.
82% accuracy cat dog prediction/loss
We will be generating an image just like above. The positions will be updated as the model learns. So you can see each and every image getting to their right (or in bad cases to the wrong) place.