First commit.

source/loadMNIST.js

@@ -0,0 +1,40 @@
+export async function loadBinary(url) {
+    const response = await fetch(url);
+    if (!response.ok) throw new Error("Failed to load " + url);
+    const buffer = await response.arrayBuffer();
+    return buffer;
+}
+
+// Loads MNIST 28x28 grayscale images + labels
+export async function loadMNIST() {
+    const imgBuf = await loadBinary("/models/MNIST-2k-images.bin");
+    const lblBuf = await loadBinary("/models/MNIST-2k-labels.bin");
+
+    const images = new Float32Array(imgBuf); // already normalized [0..1]
+    const labels = new Uint8Array(lblBuf);
+
+    const sampleCount = labels.length;
+    console.log("MNIST Loaded:", sampleCount, "samples");
+
+    return { images, labels, sampleCount };
+}
+
+// Utility visualization helper for debugging
+export function showImage(img784, canvas) {
+    const size = 28;
+    canvas.width = size;
+    canvas.height = size;
+
+    const ctx = canvas.getContext("2d");
+    const imgData = ctx.createImageData(size, size);
+
+    for (let i = 0; i < size * size; i++) {
+        const v = Math.floor(img784[i] * 255);
+        imgData.data[i * 4 + 0] = v;
+        imgData.data[i * 4 + 1] = v;
+        imgData.data[i * 4 + 2] = v;
+        imgData.data[i * 4 + 3] = 255;
+    }
+
+    ctx.putImageData(imgData, 0, 0);
+}