diff --git a/notebooks/ch04.ipynb b/notebooks/ch04.ipynb
index e6c078ba..f4ecfed2 100644
--- a/notebooks/ch04.ipynb
+++ b/notebooks/ch04.ipynb
@@ -228,49 +228,102 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 0.17576655  0.225064   -0.40083055]\n",
-      " [ 0.26364982  0.337596   -0.60124582]]\n"
+      "[[ 0.29193618  0.20277891 -0.49471508]\n",
+      " [ 0.43790426  0.30416836 -0.74207263]]\n",
+      "Hello Phoenix, this is my forked version 🚀\n"
      ]
     }
    ],
    "source": [
-    "import sys, os\n",
-    "sys.path.append(os.pardir)  # 親ディレクトリのファイルをインポートするための設定\n",
+    "import sys\n",
+    "import os\n",
+    "sys.path.append(os.pardir)  # Setting to import files from parent directory\n",
     "import numpy as np\n",
+    "from typing import Union, List, Tuple\n",
+    "# Remove ndarray from typing import and use numpy's type hints instead\n",
     "from common.functions import softmax, cross_entropy_error\n",
     "from common.gradient import numerical_gradient\n",
     "\n",
     "\n",
-    "class simpleNet:\n",
-    "    def __init__(self):\n",
-    "        self.W = np.random.randn(2,3)\n",
-    "\n",
-    "    def predict(self, x):\n",
+    "class SimpleNet:\n",
+    "    \"\"\"\n",
+    "    A simple neural network with one weight matrix.\n",
+    "    \n",
+    "    This class implements a basic neural network that can make predictions\n",
+    "    and calculate loss using softmax activation and cross-entropy error.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    def __init__(self) -> None:\n",
+    "        \"\"\"\n",
+    "        Initialize the network with random weights.\n",
+    "        \"\"\"\n",
+    "        self.W = np.random.randn(2, 3)  # Weight matrix with shape (2, 3)\n",
+    "\n",
+    "    def predict(self, x: np.ndarray) -> np.ndarray:  # Use np.ndarray instead of ndarray\n",
+    "        \"\"\"\n",
+    "        Make a prediction using the network.\n",
+    "        \n",
+    "        Args:\n",
+    "            x (np.ndarray): Input data with shape matching the first dimension of weights\n",
+    "            \n",
+    "        Returns:\n",
+    "            np.ndarray: The prediction result\n",
+    "        \"\"\"\n",
     "        return np.dot(x, self.W)\n",
     "\n",
-    "    def loss(self, x, t):\n",
+    "    def loss(self, x: np.ndarray, t: np.ndarray) -> float:  # Use np.ndarray instead of ndarray\n",
+    "        \"\"\"\n",
+    "        Calculate the loss for given input and target.\n",
+    "        \n",
+    "        Args:\n",
+    "            x (np.ndarray): Input data\n",
+    "            t (np.ndarray): Target (correct) labels\n",
+    "            \n",
+    "        Returns:\n",
+    "            float: Cross-entropy loss value\n",
+    "        \"\"\"\n",
     "        z = self.predict(x)\n",
     "        y = softmax(z)\n",
     "        loss = cross_entropy_error(y, t)\n",
-    "\n",
+    "        \n",
     "        return loss\n",
     "\n",
+    "\n",
+    "# Example usage\n",
     "x = np.array([0.6, 0.9])\n",
     "t = np.array([0, 0, 1])\n",
     "\n",
-    "net = simpleNet()\n",
+    "net = SimpleNet()\n",
     "\n",
     "f = lambda w: net.loss(x, t)\n",
     "dW = numerical_gradient(f, net.W)\n",
     "\n",
-    "print(dW)"
+    "print(dW)\n",
+    "print(\"Hello Phoenix, this is my forked version 🚀\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Hello Phoenix, this is my forked version 🚀\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Hello Phoenix, this is my forked version 🚀\")\n"
    ]
   },
   {
@@ -478,9 +531,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "dezero:Python",
+   "display_name": "Python [conda env:base] *",
    "language": "python",
-   "name": "conda-env-dezero-py"
+   "name": "conda-base-py"
   },
   "language_info": {
    "codemirror_mode": {
@@ -492,7 +545,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,