update

doc/pub/week42/ipynb/additionweek42.ipynb

@@ -678,7 +678,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "371f0a26",
    "metadata": {},
    "outputs": [
@@ -867,10 +867,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 2,
    "id": "1ce6966d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Predictions: [1, 1, 1, 1]\n"
+     ]
+    }
+   ],
    "source": [
     "import numpy as np\n",
     "class LogisticRegression:\n",
@@ -904,6 +912,14 @@
     "    predictions = model.predict(X)\n",
     "    print(\"Predictions:\", predictions)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "002ef0cd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

doc/pub/week42/ipynb/exercisesweek42.ipynb

@@ -40,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "c6f61b09",
    "metadata": {},
    "outputs": [],
@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "37f30740",
    "metadata": {},
    "outputs": [],
@@ -120,7 +120,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "b1 = ..."
+    "b1 = np.random"
    ]
   },
   {