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Merge pull request #118 from Datadote/master

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Sylvain Gugger 2020-04-18 08:08:06 -04:00 committed by GitHub
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05_pet_breeds.ipynb
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@ -77,7 +77,7 @@
"- Individual files representing items of data, such as text documents or images, possibly organised into folders or with filenames representing information about those items, or\n",
"- A table of data, such as in CSV format, where each row is an item, each row which may include filenames providing a connection between the data in the table and data in other formats such as text documents and images.\n",
"\n",
"There are exceptions to these rules, particularly in domains such as genomics, where there can be binary database formats or even network streams, but overall the vast majority of the datasets your work with use some combination of the above two formats.\n",
"There are exceptions to these rules, particularly in domains such as genomics, where there can be binary database formats or even network streams, but overall the vast majority of the datasets you work with use some combination of the above two formats.\n",
"\n",
"To see what is in our dataset we can use the ls method:"
]
@ -1264,7 +1264,7 @@
"\n",
" log(a*b) = log(a)+log(b)\n",
"\n",
"When we see it in that format looks a bit boring; but have a think about what this really means. It means that logarithms increase linearly when the underlying signal increases exponentially or multiplicatively. This is used for instance in the Richter scale of earthquake severity, and the dB scale of noise levels. It's also often used on financial charts, where we want to show compound growth rates more clearly. Computer scientists love using logarithms, because it means that modification, which can create really really large and really really small numbers, can be replaced by addition, which is much less likely to result in scales which are difficult for our computer to handle."
"When we see it in that format, it looks a bit boring; but have a think about what this really means. It means that logarithms increase linearly when the underlying signal increases exponentially or multiplicatively. This is used for instance in the Richter scale of earthquake severity, and the dB scale of noise levels. It's also often used on financial charts, where we want to show compound growth rates more clearly. Computer scientists love using logarithms, because it means that modification, which can create really really large and really really small numbers, can be replaced by addition, which is much less likely to result in scales which are difficult for our computer to handle."
]
},
{
@ -2017,7 +2017,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"This has improved our model a bit, but there's more we can do. The deepest layers of our pretrained model might not need as high a learning rate as the last ones, so we should probably use different learning rates for those, something called discriminative learning rates."
"This has improved our model a bit, but there's more we can do. The shallowest layers of our pretrained model might not need as high a learning rate as the last ones, so we should probably use different learning rates for those, something called discriminative learning rates."
]
},
{
@ -2532,6 +2532,18 @@
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
}
},
"nbformat": 4,