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This commit is contained in:
Jeremy Howard
2020-09-03 15:51:00 -07:00
parent 40a755b822
commit d67a599255
22 changed files with 669 additions and 201 deletions
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39
clean/01_intro.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *"
]
},
{
@@ -1569,6 +1581,31 @@
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
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"name": "python",
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"version": "3.7.7"
},
"toc": {
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42
clean/02_production.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *\n",
"from fastai.vision.widgets import *"
]
},
@@ -99,6 +111,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# clean\n",
"To download images with Bing Image Search, sign up at Microsoft for a free account. You will be given a key, which you can copy and enter in a cell as follows (replacing 'XXX' with your key and executing it):"
]
},
@@ -108,7 +121,7 @@
"metadata": {},
"outputs": [],
"source": [
"key = 'XXX'"
"key = os.environ.get('AZURE_SEARCH_KEY', 'XXX')"
]
},
{
@@ -1087,6 +1100,31 @@
"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": "3.7.7"
},
"toc": {
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"nav_menu": {},
"number_sections": false,
"sideBar": true,
"skip_h1_title": true,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
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"toc_section_display": true,
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},
"nbformat": 4,

37
clean/03_ethics.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "markdown",
"metadata": {},
@@ -304,6 +316,31 @@
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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39
clean/04_mnist_basics.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -8,7 +20,7 @@
"source": [
"#hide\n",
"from fastai.vision.all import *\n",
"from utils import *\n",
"from fastbook import *\n",
"\n",
"matplotlib.rc('image', cmap='Greys')"
]
@@ -4294,6 +4306,31 @@
"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": "3.7.7"
},
"toc": {
"base_numbering": 1,
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"number_sections": false,
"sideBar": true,
"skip_h1_title": true,
"title_cell": "Table of Contents",
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"toc_cell": false,
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39
clean/05_pet_breeds.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *"
]
},
{
@@ -1762,6 +1774,31 @@
"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": "3.7.7"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": true,
"skip_h1_title": true,
"title_cell": "Table of Contents",
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"toc_cell": false,
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"nbformat": 4,

353
clean/06_multicat.ipynb
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File diff suppressed because one or more lines are too long

14
clean/07_sizing_and_tta.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *"
]
},
{

39
clean/08_collab.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *"
]
},
{
@@ -1739,6 +1751,31 @@
"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": "3.7.7"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": true,
"skip_h1_title": true,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
"nbformat": 4,

39
clean/09_tabular.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -17,7 +29,7 @@
],
"source": [
"#hide\n",
"from utils import *\n",
"from fastbook import *\n",
"from kaggle import api\n",
"from pandas.api.types import is_string_dtype, is_numeric_dtype, is_categorical_dtype\n",
"from fastai.tabular.all import *\n",
@@ -8443,6 +8455,31 @@
"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": "3.7.7"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": true,
"skip_h1_title": true,
"title_cell": "Table of Contents",
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"toc_cell": false,
"toc_position": {},
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"toc_window_display": false
}
},
"nbformat": 4,

18
clean/11_midlevel_data.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *\n",
"from IPython.display import display,HTML"
]
},
@@ -619,7 +631,7 @@
"metadata": {},
"outputs": [],
"source": [
"class SiameseImage(Tuple):\n",
"class SiameseImage(fastuple):\n",
" def show(self, ctx=None, **kwargs): \n",
" img1,img2,same_breed = self\n",
" if not isinstance(img1, Tensor):\n",
@@ -860,7 +872,7 @@
"source": [
"Congratulations—you've completed all of the chapters in this book that cover the key practical parts of training models and using deep learning! You know how to use all of fastai's built-in applications, and how to customize them using the data block API and loss functions. You even know how to create a neural network from scratch, and train it! (And hopefully you now know some of the questions to ask to make sure your creations help improve society too.)\n",
"\n",
"The knowledge you already have is enough to create full working prototypes of many types of neural network application. More importantly, it will help you understand the capabilities and limitations of deep learning models, and how to design a system that's well adapted to them.\n",
"The knowledge you already have is enough to create full working prototypes of many types of neural network applications. More importantly, it will help you understand the capabilities and limitations of deep learning models, and how to design a system that's well adapted to them.\n",
"\n",
"In the rest of this book we will be pulling apart those applications, piece by piece, to understand the foundations they are built on. This is important knowledge for a deep learning practitioner, because it is what allows you to inspect and debug models that you build and create new applications that are customized for your particular projects."
]

14
clean/12_nlp_dive.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *"
]
},
{

14
clean/13_convolutions.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -8,7 +20,7 @@
"source": [
"#hide\n",
"from fastai.vision.all import *\n",
"from utils import *\n",
"from fastbook import *\n",
"\n",
"matplotlib.rc('image', cmap='Greys')"
]

14
clean/14_resnet.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -9,7 +21,7 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"from fastbook import *"
]
},
{

18
clean/15_arch_details.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *"
]
},
{
@@ -111,7 +123,7 @@
"path = untar_data(URLs.PETS)\n",
"files = get_image_files(path/\"images\")\n",
"\n",
"class SiameseImage(Tuple):\n",
"class SiameseImage(fastuple):\n",
" def show(self, ctx=None, **kwargs): \n",
" img1,img2,same_breed = self\n",
" if not isinstance(img1, Tensor):\n",
@@ -387,7 +399,7 @@
"1. What is `model_meta`? Try printing it to see what's inside.\n",
"1. Read the source code for `create_head` and make sure you understand what each line does.\n",
"1. Look at the output of `create_head` and make sure you understand why each layer is there, and how the `create_head` source created it.\n",
"1. Figure out how to change the dropout, layer size, and number of layers created by `create_cnn`, and see if you can find values that result in better accuracy from the pet recognizer.\n",
"1. Figure out how to change the dropout, layer size, and number of layers created by `cnn_learner`, and see if you can find values that result in better accuracy from the pet recognizer.\n",
"1. What does `AdaptiveConcatPool2d` do?\n",
"1. What is \"nearest neighbor interpolation\"? How can it be used to upsample convolutional activations?\n",
"1. What is a \"transposed convolution\"? What is another name for it?\n",

12
clean/17_foundations.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
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{
"cell_type": "code",
"execution_count": null,

14
clean/18_CAM.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -9,7 +21,7 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"from fastbook import *"
]
},
{

14
clean/19_learner.ipynb
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@@ -7,7 +7,19 @@
"outputs": [],
"source": [
"#hide\n",
"from utils import *"
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"from fastbook import *"
]
},
{

12
clean/20_conclusion.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "markdown",
"metadata": {},

12
clean/app_jupyter.ipynb
View File

@@ -1,5 +1,17 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#hide\n",
"!pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
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"metadata": {},