When I decided I wanted to understand neural networks (NN) I thought that each new NN was crafted from scratch with a unique structure. At the time I was disappointed to find out that NNs (outside of research looking for novel algorithms) are generally built using specialty libraries like Tensorflow and Pytorch, which allow complex neural networks to be set up in just a few lines of code. At the time it appeared to me that this took all the fun out of it.

Since then I have learned that it would be absurd to code each NN from scratch. Partly because it would be pointless to rewrite code that could be generalized for later use, and libraries like Tensorflow utilise CUDA, which allows the multithreaded GPU to perform efficient matrix computations. …

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