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Le-Zheng · May 28, 2019 · ab108f4 · ab108f4
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Showing 5 changed files with 5 additions and 15 deletions.
diff --git a/keras/3.5-classifying-movie-reviews.ipynb b/keras/3.5-classifying-movie-reviews.ipynb
@@ -484,9 +484,7 @@
     "train_loss = np.array(model.get_train_summary('Loss'))\n",
     "val_loss = np.array(model.get_validation_summary('Loss'))\n",
     "\n",
-    "import matplotlib\n",
-    "matplotlib.use('Agg')\n",
-    "from matplotlib import pyplot as plt\n",
+    "import matplotlib.pyplot as plt\n",
     "plt.plot(train_loss[:,0],train_loss[:,1],label='train loss')\n",
     "plt.plot(val_loss[:,0],val_loss[:,1],label='validation loss',color='green')\n",
     "plt.title('Training and validation loss')\n",

diff --git a/keras/3.6-classifying-newswires.ipynb b/keras/3.6-classifying-newswires.ipynb
@@ -295,9 +295,7 @@
     "train_loss = np.array(model.get_train_summary('Loss'))\n",
     "val_loss = np.array(model.get_validation_summary('Loss'))\n",
     "\n",
-    "import matplotlib\n",
-    "matplotlib.use('Agg')\n",
-    "from matplotlib import pyplot as plt\n",
+    "import matplotlib.pyplot as plt\n",
     "plt.plot(train_loss[:,0],train_loss[:,1],label='train loss')\n",
     "plt.plot(val_loss[:,0],val_loss[:,1],label='validation loss',color='green')\n",
     "plt.title('Training and validation loss')\n",

diff --git a/keras/3.7-predicting-house-prices.ipynb b/keras/3.7-predicting-house-prices.ipynb
@@ -666,9 +666,7 @@
     }
    ],
    "source": [
-    "import matplotlib\n",
-    "matplotlib.use('Agg')\n",
-    "from matplotlib import pyplot as plt\n",
+    "import matplotlib.pyplot as plt\n",
     "plt.plot(average_mae_history[:,0],average_mae_history[:,1])\n",
     "plt.xlabel('Steps')\n",
     "plt.ylabel('Validation MAE')\n",

diff --git a/keras/4.4-overfitting-and-underfitting.ipynb b/keras/4.4-overfitting-and-underfitting.ipynb
@@ -254,9 +254,7 @@
    },
    "outputs": [],
    "source": [
-    "import matplotlib\n",
-    "matplotlib.use('Agg')\n",
-    "from matplotlib import pyplot as plt\n",
+    "import matplotlib.pyplot as plt\n",
     "original_val_loss = np.array(original_model.get_validation_summary(\"Loss\"))"
    ]
   },

diff --git a/keras/6.2-understanding-recurrent-neural-networks.ipynb b/keras/6.2-understanding-recurrent-neural-networks.ipynb
@@ -307,9 +307,7 @@
     "train_loss = np.array(model.get_train_summary('Loss'))\n",
     "val_loss = np.array(model.get_validation_summary('Loss'))\n",
     "\n",
-    "import matplotlib\n",
-    "matplotlib.use('Agg')\n",
-    "from matplotlib import pyplot as plt\n",
+    "import matplotlib.pyplot as plt\n",
     "plt.plot(train_loss[:,0],train_loss[:,1],label='train loss')\n",
     "plt.plot(val_loss[:,0],val_loss[:,1],label='validation loss',color='green')\n",
     "plt.xlabel('Steps')\n",