Cross platform - cross language performance neural net designed to be embedded into code-bases
See example Athenna Repo
```Rust use athenna::nn::; use athenna::activations::;
fn main() {
println!("Testing Athenna NN");
let testfile = &"c:/data/test.athenna".tostring();
let layers:Vec
nn.learning_rate = 0.02;
let x = &vec!{0.2,0.8,0.4}; let y = &vec!{0.7,0.4,0.5};
// simulate learning and mutation
// this model will overfit as there is only one set of data
for i in 0..1000 { if i % 100 == 0 { // helps not get stuck in local minima! nn.mutate(7, 0.0001); } nn.backpropagate(x, y); } let w = nn.feedforward(x); println!("cost: {} | {} {} {}", nn.cost, w[0], w[1], w[2]); nn.save(test_file);
let mut nn = Athenna::load(testfile).unwrap(); let w = nn.feedforward(x); println!("check reloaded nn matches : {} {} {}", nn.cost, w[0], w[1], w[2]); } ```