From 62993dd59bbbfcdb07dbb5836d359fad6334f23e Mon Sep 17 00:00:00 2001
From: TinWoodman92 <chrhodgden@gmail.com>
Date: Thu, 8 Feb 2024 16:09:56 -0600
Subject: initial commit

---
 src/nnetwork.js | 36 ++++++++++++++++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 src/nnetwork.js

(limited to 'src/nnetwork.js')

diff --git a/src/nnetwork.js b/src/nnetwork.js
new file mode 100644
index 0000000..dd21491
--- /dev/null
+++ b/src/nnetwork.js
@@ -0,0 +1,36 @@
+console.log('Hello from nnetwork.js');
+
+class NNetwork {
+	constructor(nodeCounts, activationFunctionNames, learningRate) {
+		this.learningRate = learningRate;
+		this.layers = [];
+		for (let i = 1; i < nodeCounts.length; i++) {
+			this.layers.push(new Layer(nodeCounts[i-1], nodeCounts[i], activationFunctionNames[i]));
+		};
+	}
+	forwardPropogation(activationInput) {
+		let ao = activationInput;		
+		this.layers.forEach(layer => {
+			ao = layer.forwardPropogation(ao);
+		});
+		return ao;
+	}
+	backPropogation(activationInput, targetOutput) {
+		let ao = this.forwardPropogation(activationInput);
+		let cost = math.subtract(ao, targetOutput);
+		let dc_da = math.multiply(cost, 2);
+		cost = math.map(cost, element => element ** 2);
+		cost = math.sum(cost)
+		this.layers.reverse().forEach(layer => {
+			dc_da = layer.backPropogation(dc_da);
+		});
+		this.layers.reverse()
+		return cost;
+	}
+	gradientDescent() {
+		this.layers.reverse().forEach(layer => {
+			layer.gradientDescent(this.learningRate);
+		});
+		this.layers.reverse()
+	}
+};
-- 
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