Minimal automatic-differentiation engine written in Rust.Running the demo trains a tiny Multi-Layer Perceptron to learn the XOR function and writes a rendered computation graph of a single Perceptron to graph.html.use nanograd::scalar::{Scalar, func}; let x = Scalar::new_grad(2.0); let y = Scalar::new_grad(-1.0); // z = relu(x * y + 3) let z = func::relu(x.clone() * y.clone() + 3.0); z.backward(); println!("z = {}", z.get_value()); println!("dz/dx = {:?}", x.get_grad()); println!("dz/dy = {:?}",...