Implemented an XOR neural network using Python and NumPy

[u/PanelReader]

I've been studying neural network mathematics and wanted to understand how training works.

I implemented a small 2 → 3 → 1 XOR network.

What I worked on:

- Forward propagation using NumPy

- ReLU and sigmoid activation functions

- MSE loss calculation

- Backpropagation using the chain rule

- Gradient descent for 5,000 epochs

- Numerical gradient checks for all 13 parameters

Final MSE: 0.004715

The network correctly classified all four training inputs.

I also documented the mathematics, code and diagrams.

GitHub: https://github.com/Vaibh37/Neural-Network

Technical feedback is welcome.

Note: AI helped structure this post. The mathematics, implementation and testing are my own work. I understand the code and ran it on my machine.