gradients 0.3.4

An OpenCL, CUDA and CPU based Deep Learning Library
Documentation 
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use gradients::{range, LinearReg, Matrix, CPU};
use graplot::Scatter;

fn main() {
    let device = CPU::new();

    let x = Matrix::from((
        &device,
        (1, 13),
        [5., 4., 3., 6., 2., 5., 2., 9., 7., 11., 12., 13., 9.],
    )) / 17.;

    let y = Matrix::from((
        &device,
        (1, 13),
        [
            20., 40., 50., 60., 55., 100., 140., 120., 155., 85., 97., 119., 111.,
        ],
    )) / 255.;

    let mut lg = LinearReg::new(&x, &y);

    let mut loss_values = vec![0.; 401];

    for i in range(400) {
        loss_values[i] = lg.step(0.001);
    }

    /*let plot = graplot::Plot::new(loss_values);
    plot.show();*/

    let mut scatter = Scatter::new((x.read(), y.read()));
    scatter.add((|x| lg.k as f64 * x + lg.d as f64, "-b"));
    scatter.show();
}