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Commit a95142bf authored by Mark Daoust's avatar Mark Daoust
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Minor + typos

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samples/core/get_started/basic_regression.ipynb
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......@@ -5,8 +5,6 @@
"colab": {
"name": "basic-regression.ipynb",
"version": "0.3.2",
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......@@ -34,13 +32,7 @@
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......@@ -63,13 +55,7 @@
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......@@ -141,12 +127,7 @@
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......@@ -176,12 +157,7 @@
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......@@ -213,12 +189,7 @@
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......@@ -322,12 +283,7 @@
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......@@ -352,12 +308,7 @@
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......@@ -399,22 +350,17 @@
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"def build_model():\n",
" model = keras.Sequential()\n",
" \n",
" model.add(keras.layers.Dense(64, activation=tf.nn.relu,\n",
" input_shape=(train_data.shape[1],)))\n",
" model.add(keras.layers.Dense(64, activation=tf.nn.relu))\n",
" model.add(keras.layers.Dense(1))\n",
" model = keras.Sequential([\n",
" keras.layers.Dense(64, activation=tf.nn.relu, \n",
" input_shape=(train_data.shape[1],)),\n",
" keras.layers.Dense(64, activation=tf.nn.relu),\n",
" keras.layers.Dense(1)\n",
" ])\n",
"\n",
" optimizer = tf.train.RMSPropOptimizer(0.001)\n",
"\n",
......@@ -445,12 +391,7 @@
"metadata": {
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......@@ -484,12 +425,7 @@
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......@@ -500,8 +436,10 @@
" plt.figure()\n",
" plt.xlabel('Epoch')\n",
" plt.ylabel('Mean Abs Error [1000$]')\n",
" plt.plot(history.epoch, np.array(history.history['mean_absolute_error']), label='Train Loss')\n",
" plt.plot(history.epoch, np.array(history.history['val_mean_absolute_error']), label = 'Val loss')\n",
" plt.plot(history.epoch, np.array(history.history['mean_absolute_error']), \n",
" label='Train Loss')\n",
" plt.plot(history.epoch, np.array(history.history['val_mean_absolute_error']),\n",
" label = 'Val loss')\n",
" plt.legend()\n",
" plt.ylim([0,5])\n",
"\n",
......@@ -526,12 +464,7 @@
"metadata": {
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......@@ -565,12 +498,7 @@
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......@@ -597,12 +525,7 @@
"metadata": {
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......@@ -622,7 +545,7 @@
"source": [
"## Conclusion\n",
"\n",
"This notebook i a few techniques to introduce a regresson problem.\n",
"This notebook introduced a few techniques to handle a regresson problem.\n",
"\n",
"* Mean Squared Error (MSE) is a common loss function used for regression problems (different than classification problems).\n",
"* Similarly, evaluation metrics used for regression differ from classification. A common regression metric is Mean Absolute Error (MAE).\n",
......
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