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update samples from Release-139 as a part of 1.0.55 SDK release

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vizhur
2019-08-05 18:39:19 +00:00
parent e4d9a2b4c5
commit c0dae0c645
69 changed files with 6879 additions and 1147 deletions
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tutorials/img-classification-part1-training.ipynb
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@@ -218,7 +218,7 @@
"source": [
"### Display some sample images\n",
"\n",
"Load the compressed files into `numpy` arrays. Then use `matplotlib` to plot 30 random images from the dataset with their labels above them. Note this step requires a `load_data` function that's included in an `util.py` file. This file is included in the sample folder. Please make sure it is placed in the same folder as this notebook. The `load_data` function simply parses the compresse files into numpy arrays."
"Load the compressed files into `numpy` arrays. Then use `matplotlib` to plot 30 random images from the dataset with their labels above them. Note this step requires a `load_data` function that's included in an `utils.py` file. This file is included in the sample folder. Please make sure it is placed in the same folder as this notebook. The `load_data` function simply parses the compresse files into numpy arrays."
]
},
{
@@ -260,7 +260,7 @@
"\n",
"Now make the data accessible remotely by uploading that data from your local machine into Azure so it can be accessed for remote training. The datastore is a convenient construct associated with your workspace for you to upload/download data, and interact with it from your remote compute targets. It is backed by Azure blob storage account.\n",
"\n",
"The MNIST files are uploaded into a directory named `mnist` at the root of the datastore."
"The MNIST files are uploaded into a directory named `mnist` at the root of the datastore. See [access data from your datastores](https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/service/how-to-access-data) for more information."
]
},
{
@@ -674,6 +674,18 @@
"language": "python",
"name": "python36"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.6"
},
"msauthor": "roastala"
},
"nbformat": 4,