A simple implementation of a neural network in C#. The repository also contains an Excel sheet with the calculations for the network activations and the gradients.
I also created a slide deck with an explanation of the back propagation algorithm using the example from this code.
These articles and examples helped me understand the theory behind a neural network:
- Neural Network Back-Propagation Using C#
- Neural Networks and Deep Learning (free online ebook)
- How to Build a Neural Network
- Neural network with learning by backward error propagation
- A Step by Step Backpropagation Example
- Basis of Neural Networks in C#
- Machine Learning using a Neural Network written in C#
And these Youtube videos helped me to better understand what's happening in the back propagation algorithm:
From the 3Blue1Brown channel:
- But what is a Neural Network? | Chapter 1
- Gradient descent, how neural networks learn | Chapter 2
- What is backpropagation really doing? | Chapter 3
- Backpropagation calculus | Appendix to deep learning chapter 3
From the Welch Labs channel: