|
2 | 2 | author_username='dansbecker',
|
3 | 3 | course_name='Deep Learning',
|
4 | 4 | course_url='https://www.kaggle.com/learn/deep-learning',
|
5 |
| - course_forum_url='https://www.kaggle.com/learn-forum/161321' |
| 5 | + course_forum_url='https://www.kaggle.com/learn-forum/161321', |
6 | 6 | )
|
7 | 7 |
|
8 |
| -lessons = [ {'topic': topic_name} for topic_name in |
9 |
| - [ |
10 |
| - 'Intro to Deep Learning and Computer Vision', |
11 |
| - 'Building Models from Convolutions', |
12 |
| - 'TensorFlow programming', |
13 |
| - 'Transfer Learning', |
14 |
| - 'Data Augmentation', |
15 |
| - 'A Deeper Understanding of Deep Learning', |
16 |
| - 'Deep Learning from Scratch', |
17 |
| - 'Dropout and Strides for Larger Models', |
18 |
| - 'Create Your First Submission' |
19 |
| - ] |
20 |
| - ] |
| 8 | +lessons = [ {'topic': topic_name} for topic_name in [ |
| 9 | + 'Intro to Deep Learning and Computer Vision', |
| 10 | + 'Building Models from Convolutions', |
| 11 | + 'TensorFlow programming', |
| 12 | + 'Transfer Learning', |
| 13 | + 'Data Augmentation', |
| 14 | + 'A Deeper Understanding of Deep Learning', |
| 15 | + 'Deep Learning from Scratch', |
| 16 | + 'Dropout and Strides for Larger Models', |
| 17 | + 'Create Your First Submission' |
| 18 | + ] |
| 19 | +] |
21 | 20 |
|
22 | 21 | notebooks = [
|
23 | 22 | dict(
|
24 | 23 | filename='tut1_intro.ipynb',
|
25 | 24 | lesson_idx=0,
|
26 | 25 | type='tutorial',
|
27 |
| - ), |
| 26 | + docker_image_pinning_type="original", |
| 27 | + ), |
28 | 28 | dict(
|
29 |
| - filename='ex1_convolutions.ipynb', |
30 |
| - lesson_idx=0, |
31 |
| - type='exercise', |
32 |
| - scriptid=499266, |
33 |
| - dataset_sources = ["keras/resnet50"], |
34 |
| - competition_sources = ["dog-breed-identification"], |
35 |
| - ), |
| 29 | + filename='ex1_convolutions.ipynb', |
| 30 | + lesson_idx=0, |
| 31 | + type='exercise', |
| 32 | + scriptid=499266, |
| 33 | + dataset_sources=["keras/resnet50"], |
| 34 | + competition_sources=["dog-breed-identification"], |
| 35 | + docker_image_pinning_type="original", |
| 36 | + ), |
36 | 37 | dict(
|
37 | 38 | filename='tut2_building_models_from_convolutions.ipynb',
|
38 | 39 | lesson_idx=1,
|
39 | 40 | type='tutorial',
|
40 |
| - ), |
| 41 | + docker_image_pinning_type="original", |
| 42 | + ), |
41 | 43 | dict(
|
42 | 44 | filename='tut3_programming_tf_and_keras.ipynb',
|
43 | 45 | lesson_idx=2,
|
44 | 46 | type='tutorial',
|
45 |
| - dataset_sources = ["keras/resnet50"], |
46 |
| - competition_sources = ["dog-breed-identification"], |
| 47 | + dataset_sources=["keras/resnet50"], |
| 48 | + competition_sources=["dog-breed-identification"], |
| 49 | + docker_image_pinning_type="original", |
47 | 50 | ),
|
48 | 51 | dict(
|
49 | 52 | filename='ex3_programming_tf_and_keras.ipynb',
|
50 | 53 | lesson_idx=2,
|
51 | 54 | type='exercise',
|
52 |
| - enable_gpu=True, |
53 |
| - scriptid=521452, |
54 |
| - dataset_sources = [ |
55 |
| - "alexisbcook/resnet50", |
56 |
| - "alexisbcook/vgg16", |
57 |
| - "dansbecker/hot-dog-not-hot-dog" |
58 |
| - ], |
| 55 | + enable_gpu=True, |
| 56 | + scriptid=521452, |
| 57 | + dataset_sources = [ |
| 58 | + "alexisbcook/resnet50", |
| 59 | + "alexisbcook/vgg16", |
| 60 | + "dansbecker/hot-dog-not-hot-dog" |
| 61 | + ], |
| 62 | + docker_image_pinning_type="original", |
59 | 63 | ),
|
60 | 64 | dict(
|
61 | 65 | filename='tut4_transfer_learning.ipynb',
|
62 | 66 | lesson_idx=3,
|
63 | 67 | type='tutorial',
|
64 |
| - dataset_sources = [ |
65 |
| - "keras/resnet50", |
66 |
| - "dansbecker/urban-and-rural-photos" |
67 |
| - ], |
| 68 | + dataset_sources = [ |
| 69 | + "keras/resnet50", |
| 70 | + "dansbecker/urban-and-rural-photos" |
| 71 | + ], |
| 72 | + docker_image_pinning_type="original", |
68 | 73 | ),
|
69 | 74 | dict(
|
70 | 75 | filename='ex4_transfer_learning.ipynb',
|
71 | 76 | lesson_idx=3,
|
72 | 77 | type='exercise',
|
73 |
| - scriptid=532365, |
74 |
| - dataset_sources = [ |
75 |
| - "alexisbcook/resnet50", |
76 |
| - "dansbecker/dogs-gone-sideways" |
77 |
| - ], |
78 |
| - enable_gpu=True, |
| 78 | + scriptid=532365, |
| 79 | + dataset_sources = [ |
| 80 | + "alexisbcook/resnet50", |
| 81 | + "dansbecker/dogs-gone-sideways" |
| 82 | + ], |
| 83 | + enable_gpu=True, |
| 84 | + docker_image_pinning_type="original", |
79 | 85 | ),
|
80 | 86 | dict(
|
81 | 87 | filename='tut5_data_augmentation.ipynb',
|
82 | 88 | lesson_idx=4,
|
83 | 89 | type='tutorial',
|
84 |
| - dataset_sources = [ |
85 |
| - "keras/resnet50", |
86 |
| - "dansbecker/urban-and-rural-photos", |
87 |
| - ], |
| 90 | + dataset_sources = [ |
| 91 | + "keras/resnet50", |
| 92 | + "dansbecker/urban-and-rural-photos", |
| 93 | + ], |
| 94 | + docker_image_pinning_type="original", |
88 | 95 | ),
|
89 | 96 | dict(
|
90 | 97 | filename='ex5_data_augmentation.ipynb',
|
91 | 98 | lesson_idx=4,
|
92 | 99 | type='exercise',
|
93 |
| - enable_gpu=True, |
94 |
| - scriptid=536195, |
| 100 | + enable_gpu=True, |
| 101 | + scriptid=536195, |
95 | 102 | dataset_sources = [
|
96 |
| - "alexisbcook/resnet50", |
97 |
| - "dansbecker/dogs-gone-sideways" |
98 |
| - ], |
99 |
| - ), |
| 103 | + "alexisbcook/resnet50", |
| 104 | + "dansbecker/dogs-gone-sideways" |
| 105 | + ], |
| 106 | + docker_image_pinning_type="original", |
| 107 | + ), |
100 | 108 | dict(
|
101 | 109 | filename='tut6_deep_understanding.ipynb',
|
102 | 110 | lesson_idx=5,
|
103 | 111 | type='tutorial',
|
104 |
| - ), |
| 112 | + docker_image_pinning_type="original", |
| 113 | + ), |
105 | 114 | dict(filename='tut7_dl_from_scratch.ipynb',
|
106 | 115 | lesson_idx=6,
|
107 | 116 | type='tutorial',
|
108 |
| - dataset_sources = ['zalando-research/fashionmnist'], |
109 |
| - competition_sources=['digit-recognizer'], |
110 |
| - ), |
| 117 | + dataset_sources=['zalando-research/fashionmnist'], |
| 118 | + competition_sources=['digit-recognizer'], |
| 119 | + docker_image_pinning_type="original", |
| 120 | + ), |
111 | 121 | dict(
|
112 | 122 | filename='ex7_from_scratch.ipynb',
|
113 | 123 | lesson_idx=6,
|
114 |
| - enable_gpu=True, |
| 124 | + enable_gpu=True, |
115 | 125 | type='exercise',
|
116 | 126 | scriptid=574269,
|
117 |
| - competition_sources=['digit-recognizer'], |
118 |
| - dataset_sources = ['zalando-research/fashionmnist'], |
119 |
| - ), |
| 127 | + competition_sources=['digit-recognizer'], |
| 128 | + dataset_sources=['zalando-research/fashionmnist'], |
| 129 | + docker_image_pinning_type="original", |
| 130 | + ), |
120 | 131 | dict(
|
121 | 132 | filename='tut8_dropout_and_strides.ipynb',
|
122 | 133 | lesson_idx=7,
|
123 | 134 | type='tutorial',
|
124 |
| - competition_sources=['digit-recognizer'], |
125 |
| - dataset_sources = ['zalando-research/fashionmnist'], |
126 |
| - ), |
| 135 | + competition_sources=['digit-recognizer'], |
| 136 | + dataset_sources=['zalando-research/fashionmnist'], |
| 137 | + docker_image_pinning_type="original", |
| 138 | + ), |
127 | 139 | dict(
|
128 | 140 | filename='ex8_dropout_strides.ipynb',
|
129 | 141 | lesson_idx=7,
|
130 |
| - enable_gpu=True, |
| 142 | + enable_gpu=True, |
131 | 143 | type='exercise',
|
132 |
| - scriptid=663261, |
133 |
| - competition_sources=['digit-recognizer'], |
134 |
| - dataset_sources = ['zalando-research/fashionmnist'], |
135 |
| - ), |
| 144 | + scriptid=663261, |
| 145 | + competition_sources=['digit-recognizer'], |
| 146 | + dataset_sources=['zalando-research/fashionmnist'], |
| 147 | + docker_image_pinning_type="original", |
| 148 | + ), |
136 | 149 | dict(
|
137 | 150 | filename='tut_tpus.ipynb',
|
138 | 151 | lesson_idx=8,
|
139 | 152 | type='tutorial',
|
140 | 153 | competition_sources=['tpu-getting-started'],
|
141 |
| - enable_internet=True |
142 |
| - ), |
| 154 | + enable_internet=True, |
| 155 | + docker_image_pinning_type="original", |
| 156 | + ), |
143 | 157 | dict(
|
144 | 158 | filename='ex_tpus.ipynb',
|
145 | 159 | lesson_idx=8,
|
146 | 160 | type='exercise',
|
147 | 161 | scriptid=10204702,
|
148 | 162 | competition_sources=['tpu-getting-started'],
|
149 |
| - enable_internet=True |
150 |
| - ) |
151 |
| - ] |
| 163 | + enable_internet=True, |
| 164 | + docker_image_pinning_type="original", |
| 165 | + ) |
| 166 | +] |
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