Merge pull request #2730 from manishchaudhari-ssk/cbl337-notebook-updates

Notebook updates - OCBL337-ClassifyingImagesWithTransferLearning

Author: 0yster

courses/machine_learning/deepdive2/computer_vision_fun/labs/classifying_images_with_transfer_learning.ipynb

@@ -33,7 +33,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2.6.0\n"
+      "2.11.0\n"
      ]
     }
    ],
@@ -189,11 +189,11 @@
     "  regularizer = tf.keras.regularizers.l1_l2(l1, l2)\n",
     "\n",
     "  train_dataset = (tf.data.TextLineDataset(\n",
-    "      \"gs://practical-ml-vision-book/flowers_5_jpeg/flower_photos/train_set.csv\").\n",
+    "      \"gs://cloud-training-demos/practical-ml-vision-book-data/flowers_5_jpeg/flower_photos/train_set.csv\").\n",
     "      map(decode_csv)).batch(batch_size)\n",
     "\n",
     "  eval_dataset = (tf.data.TextLineDataset(\n",
-    "      \"gs://practical-ml-vision-book/flowers_5_jpeg/flower_photos/eval_set.csv\").\n",
+    "      \"gs://cloud-training-demos/practical-ml-vision-book-data/flowers_5_jpeg/flower_photos/eval_set.csv\").\n",
     "      map(decode_csv)).batch(32) # this doesn't matter\n",
     "\n",
     "  layers = [\n",
@@ -330,7 +330,7 @@
     }
    ],
    "source": [
-    "plot_predictions(model, \"gs://practical-ml-vision-book/flowers_5_jpeg/flower_photos/eval_set.csv\")"
+    "plot_predictions(model, \"gs://cloud-training-demos/practical-ml-vision-book-data/flowers_5_jpeg/flower_photos/eval_set.csv\")"
    ]
   }
  ],

courses/machine_learning/deepdive2/computer_vision_fun/solutions/classifying_images_with_transfer_learning.ipynb

@@ -33,7 +33,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2.6.0\n"
+      "2.11.0\n"
      ]
     }
    ],
@@ -189,11 +189,11 @@
     "  regularizer = tf.keras.regularizers.l1_l2(l1, l2)\n",
     "\n",
     "  train_dataset = (tf.data.TextLineDataset(\n",
-    "      \"gs://practical-ml-vision-book/flowers_5_jpeg/flower_photos/train_set.csv\").\n",
+    "      \"gs://cloud-training-demos/practical-ml-vision-book-data/flowers_5_jpeg/flower_photos/train_set.csv\").\n",
     "      map(decode_csv)).batch(batch_size)\n",
     "\n",
     "  eval_dataset = (tf.data.TextLineDataset(\n",
-    "      \"gs://practical-ml-vision-book/flowers_5_jpeg/flower_photos/eval_set.csv\").\n",
+    "      \"gs://cloud-training-demos/practical-ml-vision-book-data/flowers_5_jpeg/flower_photos/eval_set.csv\").\n",
     "      map(decode_csv)).batch(32) # this doesn't matter\n",
     "\n",
     "  layers = [\n",
@@ -330,7 +330,7 @@
     }
    ],
    "source": [
-    "plot_predictions(model, \"gs://practical-ml-vision-book/flowers_5_jpeg/flower_photos/eval_set.csv\")"
+    "plot_predictions(model, \"gs://cloud-training-demos/practical-ml-vision-book-data/flowers_5_jpeg/flower_photos/eval_set.csv\")"
    ]
   }
  ],