🧠 Tiny XOR Neural Network in Rust

A minimalist, fully handcrafted neural network built in pure Rust — trained to solve the classic XOR problem. No frameworks, no magic — just neurons, layers, and backpropagation.

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✨ Features

• ✅ Feedforward neural network (MLP)
• ✅ Manual backpropagation implementation
• ✅ Learns XOR from scratch
• ✅ Only uses rand crate — no ML dependencies
• ✅ Fully commented and beginner-friendly

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🧠 What it learns

The XOR logic gate:

Input A	Input B	Expected Output
0	0	0
0	1	1
1	0	1
1	1	0

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🚀 Getting Started

git clone https://github.com/your-username/rust-xor-mlp.git
cd rust-xor-mlp
cargo run --release

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🔧 Configuration

You can tweak the training parameters in main.rs:

let mut network = Network::new(2, 2); // hidden layer size
network.train(100_000, 0.1); // epochs, learning rate

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📈 Sample Output (after training)

Input: [0.0, 0.0] → Output: 0.02 (Expected: 0)
Input: [0.0, 1.0] → Output: 0.97 (Expected: 1)
Input: [1.0, 0.0] → Output: 0.98 (Expected: 1)
Input: [1.0, 1.0] → Output: 0.03 (Expected: 0)