deep

examples/classification/convolution_based.ipynb

@@ -218,7 +218,7 @@
    },
    "source": [
     "The ``MiniRocketClassifier`` [2] uses the ``MiniRocket`` transform, a fast version of\n",
-    "``Rocket`` that uses hard coded convolutions and only uses PPV.  \n",
+    "``Rocket`` that uses hard coded convolutions and only uses PPV.\n",
     "MultiROCKET [3]\n",
     "adds three new pooling operations extracted from each\n",
     " kernel: mean of positive values (MPV), mean of indices of positive values (MIPV) and\n",

examples/classification/deep_learning.ipynb

@@ -10,8 +10,7 @@
     "The networks that are common to classification, regression and clustering are in the\n",
     "`networks` module. Our deep learning classifiers are based those used in deep\n",
     "learning bake off [1] and recent experimentation [2]. [3] provides an extensive recent\n",
-    "review of related deep learning work.\n",
-    "review of related deep learning work."
+    "review of related deep learning work.\n"
    ]
   },
   {
@@ -52,7 +51,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m65/65\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step\n"
+      "\u001B[1m65/65\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m0s\u001B[0m 2ms/step\n"
      ]
     },
     {
@@ -97,11 +96,11 @@
     "\n",
     "<img src=\"./img/resnet.png\" width=\"600\" alt=\"ROCKET.\">\n",
     "\n",
-    "The InceptionTime deep learning algorithm Subsequent to [1],\n",
-    "InceptionTime is an ensemble of five SingleInceptionTime deep learning\n",
-    "classifiers. Each base classifier shares the same architecture based on\n",
-    "Inception modules. Diversity is achieved through randomly intialising weights.\n",
-    "A SingleInceptionTimeClassifier has the following structure.\n",
+    "The Inception Time deep learning algorithm was proposed subsequent to [1].\n",
+    "``InceptionTimeClassifier`` is an ensemble of five ``SingleInceptionTimeClassifier``\n",
+    "deep learning classifiers. Each base classifier shares the same architecture based on\n",
+    "Inception modules. Diversity is achieved through randomly initialising weights.\n",
+    "A ``SingleInceptionTimeClassifier`` has the following structure.\n",
     "\n",
     "<img src=\"./img/inception_module.png\" width=\"600\" alt=\"ROCKET.\">\n",
     "\n",