diff --git a/04_training_linear_models.ipynb b/04_training_linear_models.ipynb
index 45701e7..8683246 100644
--- a/04_training_linear_models.ipynb
+++ b/04_training_linear_models.ipynb
@@ -709,11 +709,11 @@
     "    polybig_features = PolynomialFeatures(degree=degree, include_bias=False)\n",
     "    std_scaler = StandardScaler()\n",
     "    lin_reg = LinearRegression()\n",
-    "    polynomial_regression = Pipeline((\n",
+    "    polynomial_regression = Pipeline([\n",
     "            (\"poly_features\", polybig_features),\n",
     "            (\"std_scaler\", std_scaler),\n",
     "            (\"lin_reg\", lin_reg),\n",
-    "        ))\n",
+    "        ])\n",
     "    polynomial_regression.fit(X, y)\n",
     "    y_newbig = polynomial_regression.predict(X_new)\n",
     "    plt.plot(X_new, y_newbig, style, label=str(degree), linewidth=width)\n",
@@ -786,10 +786,10 @@
    "source": [
     "from sklearn.pipeline import Pipeline\n",
     "\n",
-    "polynomial_regression = Pipeline((\n",
+    "polynomial_regression = Pipeline([\n",
     "        (\"poly_features\", PolynomialFeatures(degree=10, include_bias=False)),\n",
     "        (\"lin_reg\", LinearRegression()),\n",
-    "    ))\n",
+    "    ])\n",
     "\n",
     "plot_learning_curves(polynomial_regression, X, y)\n",
     "plt.axis([0, 80, 0, 3])           # not shown\n",
@@ -829,11 +829,11 @@
     "    for alpha, style in zip(alphas, (\"b-\", \"g--\", \"r:\")):\n",
     "        model = model_class(alpha, **model_kargs) if alpha > 0 else LinearRegression()\n",
     "        if polynomial:\n",
-    "            model = Pipeline((\n",
+    "            model = Pipeline([\n",
     "                    (\"poly_features\", PolynomialFeatures(degree=10, include_bias=False)),\n",
     "                    (\"std_scaler\", StandardScaler()),\n",
     "                    (\"regul_reg\", model),\n",
-    "                ))\n",
+    "                ])\n",
     "        model.fit(X, y)\n",
     "        y_new_regul = model.predict(X_new)\n",
     "        lw = 2 if alpha > 0 else 1\n",
@@ -973,10 +973,10 @@
     "\n",
     "X_train, X_val, y_train, y_val = train_test_split(X[:50], y[:50].ravel(), test_size=0.5, random_state=10)\n",
     "\n",
-    "poly_scaler = Pipeline((\n",
+    "poly_scaler = Pipeline([\n",
     "        (\"poly_features\", PolynomialFeatures(degree=90, include_bias=False)),\n",
     "        (\"std_scaler\", StandardScaler()),\n",
-    "    ))\n",
+    "    ])\n",
     "\n",
     "X_train_poly_scaled = poly_scaler.fit_transform(X_train)\n",
     "X_val_poly_scaled = poly_scaler.transform(X_val)\n",