diff --git a/examples/brewing-logreg.ipynb b/examples/brewing-logreg.ipynb
index c053b73b39f..0f87185a35b 100644
--- a/examples/brewing-logreg.ipynb
+++ b/examples/brewing-logreg.ipynb
@@ -73,12 +73,12 @@
     ")\n",
     "\n",
     "# Split into train and test\n",
-    "X, Xt, y, yt = sklearn.cross_validation.train_test_split(X, y)\n",
+    "X, Xt, y, yt = sklearn.model_selection.train_test_split(X, y)\n",
     "\n",
     "# Visualize sample of the data\n",
     "ind = np.random.permutation(X.shape[0])[:1000]\n",
     "df = pd.DataFrame(X[ind])\n",
-    "_ = pd.scatter_matrix(df, figsize=(9, 9), diagonal='kde', marker='o', s=40, alpha=.4, c=y[ind])"
+    "_ = pd.plotting.scatter_matrix(df, figsize=(9, 9), diagonal='kde', marker='o', s=40, alpha=.4, c=y[ind])"
    ]
   },
   {
@@ -111,7 +111,7 @@
     "%%timeit\n",
     "# Train and test the scikit-learn SGD logistic regression.\n",
     "clf = sklearn.linear_model.SGDClassifier(\n",
-    "    loss='log', n_iter=1000, penalty='l2', alpha=5e-4, class_weight='auto')\n",
+    "    loss='log', n_iter=1000, penalty='l2', alpha=5e-4, class_weight='balanced')\n",
     "\n",
     "clf.fit(X, y)\n",
     "yt_pred = clf.predict(Xt)\n",