Adding more functionality to Model class | Let's learn - Neural networks from scratch in Go - 44

So I continue to implement Model class (well, struct in Go) that is configurable and handles whole training and prediction process. Today's progress is about invention of LayerInput, making Forward method for model and partial implementation of train flow
We study the book nnfs.io and implementing all the code with Golang instead of Python. The aim is to learn how neural networks are made inside and how it looks like to build is fully from the scratch without using frameworks like pytorch or tensorflow. We’ll have to find alternative in Go or reimplement some operations fully from the ground.
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