1 files changed, 29 insertions, 1 deletions
diff --git a/projects/autograd.md b/projects/autograd.md
index e382112..e3259d2 100644
--- a/projects/autograd.md
+++ b/projects/autograd.md
@@ -3,6 +3,34 @@ description = An implementation of autograd / backpropagation.
 languages = Python
 url = /projects/autograd
 template = project.html
+link = https://github.com/compromyse/autograd
+linklabel = SOURCE
 ---
 
-# Autograd
+All you need to run a simple neural network using autograd is the following code:
+
+The code defines a data set `X`, expected output (or ground truth) `y`. It then trains the neural network by performing backward propagation (`.backward()`), then applies the calculated gradients through `.optimise()` along with a learning rate of `0.01`.
+
+```py
+from src.nn import MLP
+from src.loss import mse
+
+X = [
+    [ 0.0, 1.0, 2.0 ],
+    [ 2.0, 1.0, 0.0 ],
+    [ 2.0, 2.0, 2.0 ],
+    [ 3.0, 3.0, 3.0 ]
+]
+
+y = [ 1.0, -1.0, 1.0, -1.0 ]
+n = MLP(3, [ 4, 4, 1 ])
+
+for i in range(400):
+    pred = [ n(x) for x in X ]
+    loss = mse(y, pred)
+    loss.zero_grad()
+    loss.backward()
+    n.optimise(0.01)
+
+print(pred)
+```