Neural networks are often presented as black boxes, hidden behind high-level libraries and abstract concepts.
In this article, we build a neural network classifier from scratch using Excel, with every computation written explicitly.
Starting from forward propagation and ending with backpropagation, we show how the model is defined as a simple mathematical function and how its parameters are learned using gradient descent. No shortcuts, no hidden steps, just the mechanics that make neural networks work.
The post The Machine Learning “Advent Calendar” Day 18: Neural Network Classifier in Excel appeared first on Towards Data Science. Read More
