Neural networks from scratch

Creating complex neural networks with different architectures in Python should be a standard practice for any machine learning engineer or data scientist. But a genuine understanding of how a neural network works is equally valuable. In this article, learn the fundamentals of how you can build neural networks without the help of the frameworks that might make it easier to use. While reading the article, you can open the notebook on GitHub and run the code at the same time. In this article, I explain how to make a basic deep neural network by implementing the forward and backward pass (backpropagation). This requires some specific knowledge about the functions of neural networks, which I discuss in this introduction to neural networks.