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https://github.com/Azure/MachineLearningNotebooks.git
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Tutorial fixes
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@@ -64,7 +64,7 @@
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},
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},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"%matplotlib inline\n",
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"%matplotlib notebook\n",
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"import numpy as np\n",
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"import numpy as np\n",
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"import matplotlib\n",
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"import matplotlib\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib.pyplot as plt\n",
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@@ -201,13 +201,6 @@
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"Download the MNIST dataset and save the files into a `data` directory locally. Images and labels for both training and testing are downloaded."
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"Download the MNIST dataset and save the files into a `data` directory locally. Images and labels for both training and testing are downloaded."
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]
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]
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},
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": null,
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@@ -97,7 +97,7 @@
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},
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},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"%matplotlib inline\n",
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"%matplotlib notebook\n",
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"import numpy as np\n",
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"import numpy as np\n",
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"import matplotlib\n",
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"import matplotlib\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib.pyplot as plt\n",
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@@ -480,7 +480,7 @@
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"test_samples = bytes(test_samples, encoding = 'utf8')\n",
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"test_samples = bytes(test_samples, encoding = 'utf8')\n",
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"\n",
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"\n",
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"# predict using the deployed model\n",
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"# predict using the deployed model\n",
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"result = json.loads(service.run(input_data=test_samples))\n",
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"result = service.run(input_data=test_samples)\n",
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"\n",
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"\n",
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"# compare actual value vs. the predicted values:\n",
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"# compare actual value vs. the predicted values:\n",
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"i = 0\n",
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"i = 0\n",
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