Update

notebooks/03_ml_basics_ex_3_mlp_clothing.ipynb

@@ -3,7 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d63563a8",
+   "id": "6c180d4b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,7 +16,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "062f7519",
+   "id": "b0e31b9c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -29,7 +29,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4ccb3a5e",
+   "id": "1ae1412e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -40,7 +40,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e5ede535",
+   "id": "f8814914",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -52,7 +52,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "39c100c1",
+   "id": "2810da39",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65,7 +65,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e267a290",
+   "id": "96f7ff8a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -93,7 +93,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7dae353a",
+   "id": "a3fe609c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -111,7 +111,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bd237a4b",
+   "id": "cf6c978d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -122,7 +122,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "169fc8c4",
+   "id": "97fc2313",
    "metadata": {
     "scrolled": true
    },
@@ -136,7 +136,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7f2e657a",
+   "id": "ef5f19d0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -164,7 +164,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "298ac3bc",
+   "id": "c0ebddc4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -183,7 +183,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9a0355ec",
+   "id": "9175d533",
    "metadata": {
     "scrolled": true
    },
@@ -194,10 +194,10 @@
     "y_pred = np.argmax(y_pred, axis=1)\n",
     "\n",
     "# Plot some examples from the test set and their predictions\n",
-    "fig, axes = plt.subplots(4, 4, figsize=(14, 14))\n",
+    "fig, axes = plt.subplots(4, 4, figsize=(18, 18))\n",
     "for i, ax in enumerate(axes.ravel()):\n",
     "    ax.matshow(x_test[i].reshape(28, 28), cmap='gray')\n",
-    "    ax.set_title(\"True: %d\\nPredict: %d\" % (np.argmax(y_test[i]), y_pred[i]))\n",
+    "    ax.set_title(\"True: %d\\nPredict: %d\" % (y_test[i], y_pred[i]))\n",
     "    ax.axis(\"off\")\n",
     "\n",
     "plt.show()"
@@ -206,7 +206,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "facda3d1",
+   "id": "4a6e85be",
    "metadata": {},
    "outputs": [],
    "source": []