Backpropagation is a common method for training a neural network. There is no shortage of papers online that attempt to explain how backpropagation works, but few that include an example with actual numbers. This post is my attempt to explain how it works with a concrete example that folks can compare their own calculations to in order to ensure they understand backpropagation correctly.
If this kind of thing interests you, you should sign up for my newsletter where I post about AI-related projects that I’m working on.
Backpropagation in Python
You can play around with a Python script that I wrote that implements the backpropagation algorithm in this Github repo.
For an interactive visualization showing a neural network as it learns, check out my Neural Network visualization.
If you find this tutorial useful and want to continue learning about neural networks, machine learning, and…
View original post 1,794 more words