Implement a Neural Network from Scratch with NumPy

Author(s): Dorian Lazar

Originally published on Towards AI.

Background image source: Wikimedia Commons

I think that the best way to really understand how a neural network works is to implement one from scratch. That is exactly what I going to do through this article. I will create a neural network class, and I want to design it in such a way to be more flexible. I do not want to hardcode in it a specific activation or loss functions, or optimizers (that is SGD, Adam, or other gradient-based methods). I will design it to receive these from outside the class so that one can just take the class’s code… Read the full blog for free on Medium.

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Published via Towards AI