{0: 'tench, Tinca tinca',
1: 'goldfish, Carassius auratus',
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
3: 'tiger shark, Galeocerdo cuvieri',
4: 'hammerhead, hammerhead shark',
5: 'electric ray, crampfish, numbfish, torpedo',
6: 'stingray',
7: 'cock',
8: 'hen',
9: 'ostrich, Struthio camelus',
10: 'brambling, Fringilla montifringilla',
11: 'goldfinch, Carduelis carduelis',
12: 'house finch, linnet, Carpodacus mexicanus',
13: 'junco, snowbird',
14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea',
15: 'robin, American robin, Turdus migratorius',
16: 'bulbul',
17: 'jay',
18: 'magpie',
19: 'chickadee',
20: 'water ouzel, dipper',
21: 'kite',
22: 'bald eagle, American eagle, Haliaeetus leucocephalus',
23: 'vulture',
24: 'great grey owl, great gray owl, Strix nebulosa',
25: 'European fire salamander, Salamandra salamandra',
26: 'common newt, Triturus vulgaris',
27: 'eft',
28: 'spotted salamander, Ambystoma maculatum',
29: 'axolotl, mud puppy, Ambystoma mexicanum',
30: 'bullfrog, Rana catesbeiana',
31: 'tree frog, tree-frog',
32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui',
33: 'loggerhead, loggerhead turtle, Caretta caretta',
34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea',
35: 'mud turtle',
36: 'terrapin',
37: 'box turtle, box tortoise',
38: 'banded gecko',
39: 'common iguana, iguana, Iguana iguana',
40: 'American chameleon, anole, Anolis carolinensis',
41: 'whiptail, whiptail lizard',
42: 'agama',
43: 'frilled lizard, Chlamydosaurus kingi',
44: 'alligator lizard',
45: 'Gila monster, Heloderma suspectum',
46: 'green lizard, Lacerta viridis',
47: 'African chameleon, Chamaeleo chamaeleon',
48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis',
49: 'African crocodile, Nile crocodile, Crocodylus niloticus',
50: 'American alligator, Alligator mississipiensis',
51: 'triceratops',
52: 'thunder snake, worm snake, Carphophis amoenus',
53: 'ringneck snake, ring-necked snake, ring snake',
54: 'hognose snake, puff adder, sand viper',
55: 'green snake, grass snake',
56: 'king snake, kingsnake',
57: 'garter snake, grass snake',
58: 'water snake',
59: 'vine snake',
60: 'night snake, Hypsiglena torquata',
61: 'boa constrictor, Constrictor constrictor',
62: 'rock python, rock snake, Python sebae',
63: 'Indian cobra, Naja naja',
64: 'green mamba',
65: 'sea snake',
66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus',
67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus',
68: 'sidewinder, horned rattlesnake, Crotalus cerastes',
69: 'trilobite',
70: 'harvestman, daddy longlegs, Phalangium opilio',
71: 'scorpion',
72: 'black and gold garden spider, Argiope aurantia',
73: 'barn spider, Araneus cavaticus',
74: 'garden spider, Aranea diademata',
75: 'black widow, Latrodectus mactans',
76: 'tarantula',
77: 'wolf spider, hunting spider',
78: 'tick',
79: 'centipede',
80: 'black grouse',
81: 'ptarmigan',
82: 'ruffed grouse, partridge, Bonasa umbellus',
83: 'prairie chicken, prairie grouse, prairie fowl',
84: 'peacock',
85: 'quail',
86: 'partridge',
87: 'African grey, African gray, Psittacus erithacus',
88: 'macaw',
89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita',
90: 'lorikeet',
91: 'coucal',
92: 'bee eater',
93: 'hornbill',
94: 'hummingbird',
95: 'jacamar',
96: 'toucan',
97: 'drake',
98: 'red-breasted merganser, Mergus serrator',
99: 'goose',
100: 'black swan, Cygnus atratus',
101: 'tusker',
102: 'echidna, spiny anteater, anteater',
103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus',
104: 'wallaby, brush kangaroo',
105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus',
106: 'wombat',
107: 'jellyfish',
108: 'sea anemone, anemone',
109: 'brain coral',
110: 'flatworm, platyhelminth',
111: 'nematode, nematode worm, roundworm',
112: 'conch',
113: 'snail',
114: 'slug',
115: 'sea slug, nudibranch',
116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore',
117: 'chambered nautilus, pearly nautilus, nautilus',
118: 'Dungeness crab, Cancer magister',
119: 'rock crab, Cancer irroratus',
120: 'fiddler crab',
121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica',
122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus',
123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish',
124: 'crayfish, crawfish, crawdad, crawdaddy',
125: 'hermit crab',
126: 'isopod',
127: 'white stork, Ciconia ciconia',
128: 'black stork, Ciconia nigra',
129: 'spoonbill',
130: 'flamingo',
131: 'little blue heron, Egretta caerulea',
132: 'American egret, great white heron, Egretta albus',
133: 'bittern',
134: 'crane',
135: 'limpkin, Aramus pictus',
136: 'European gallinule, Porphyrio porphyrio',
137: 'American coot, marsh hen, mud hen, water hen, Fulica americana',
138: 'bustard',
139: 'ruddy turnstone, Arenaria interpres',
140: 'red-backed sandpiper, dunlin, Erolia alpina',
141: 'redshank, Tringa totanus',
142: 'dowitcher',
143: 'oystercatcher, oyster catcher',
144: 'pelican',
145: 'king penguin, Aptenodytes patagonica',
146: 'albatross, mollymawk',
147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus',
148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca',
149: 'dugong, Dugong dugon',
150: 'sea lion',
151: 'Chihuahua',
152: 'Japanese spaniel',
153: 'Maltese dog, Maltese terrier, Maltese',
154: 'Pekinese, Pekingese, Peke',
155: 'Shih-Tzu',
156: 'Blenheim spaniel',
157: 'papillon',
158: 'toy terrier',
159: 'Rhodesian ridgeback',
160: 'Afghan hound, Afghan',
161: 'basset, basset hound',
162: 'beagle',
163: 'bloodhound, sleuthhound',
164: 'bluetick',
165: 'black-and-tan coonhound',
166: 'Walker hound, Walker foxhound',
167: 'English foxhound',
168: 'redbone',
169: 'borzoi, Russian wolfhound',
170: 'Irish wolfhound',
171: 'Italian greyhound',
172: 'whippet',
173: 'Ibizan hound, Ibizan Podenco',
174: 'Norwegian elkhound, elkhound',
175: 'otterhound, otter hound',
176: 'Saluki, gazelle hound',
177: 'Scottish deerhound, deerhound',
178: 'Weimaraner',
179: 'Staffordshire bullterrier, Staffordshire bull terrier',
180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier',
181: 'Bedlington terrier',
182: 'Border terrier',
183: 'Kerry blue terrier',
184: 'Irish terrier',
185: 'Norfolk terrier',
186: 'Norwich terrier',
187: 'Yorkshire terrier',
188: 'wire-haired fox terrier',
189: 'Lakeland terrier',
190: 'Sealyham terrier, Sealyham',
191: 'Airedale, Airedale terrier',
192: 'cairn, cairn terrier',
193: 'Australian terrier',
194: 'Dandie Dinmont, Dandie Dinmont terrier',
195: 'Boston bull, Boston terrier',
196: 'miniature schnauzer',
197: 'giant schnauzer',
198: 'standard schnauzer',
199: 'Scotch terrier, Scottish terrier, Scottie',
200: 'Tibetan terrier, chrysanthemum dog',
201: 'silky terrier, Sydney silky',
202: 'soft-coated wheaten terrier',
203: 'West Highland white terrier',
204: 'Lhasa, Lhasa apso',
205: 'flat-coated retriever',
206: 'curly-coated retriever',
207: 'golden retriever',
208: 'Labrador retriever',
209: 'Chesapeake Bay retriever',
210: 'German short-haired pointer',
211: 'vizsla, Hungarian pointer',
212: 'English setter',
213: 'Irish setter, red setter',
214: 'Gordon setter',
215: 'Brittany spaniel',
216: 'clumber, clumber spaniel',
217: 'English springer, English springer spaniel',
218: 'Welsh springer spaniel',
219: 'cocker spaniel, English cocker spaniel, cocker',
220: 'Sussex spaniel',
221: 'Irish water spaniel',
222: 'kuvasz',
223: 'schipperke',
224: 'groenendael',
225: 'malinois',
226: 'briard',
227: 'kelpie',
228: 'komondor',
229: 'Old English sheepdog, b
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用于在 Amazon SageMaker 上训练和部署机器学习模型的库.zip
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py:1188个
rst:167个
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SageMaker Python SDK SageMaker Python SDK 是一个开源库,用于在 Amazon SageMaker 上训练和部署机器学习模型。借助该开发工具包,您可以使用流行的深度学习框架Apache MXNet和TensorFlow来训练和部署模型。您还可以使用Amazon 算法来训练和部署模型,这些算法是针对 SageMaker 和 GPU 训练进行了优化的核心机器学习算法的可扩展实现。如果您将自己的算法内置到与 SageMaker 兼容的 Docker 容器中,您也可以使用这些算法来训练和托管模型。有关详细文档(包括 API 参考),请参阅阅读文档。目录安装 SageMaker Python SDK使用 SageMaker Python SDK使用 MXNet使用 TensorFlow使用 Chainer使用 PyTorch使用 Scikit-learn使用 XGBoostSageMaker 强化学习估算器SageMaker SparkML 服务Amazon SageMaker 内置算法估算器使用 Sage
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用于在 Amazon SageMaker 上训练和部署机器学习模型的库.zip (1693个子文件)
2-CLAUSE-BSD 1KB
abalone 311B
abalone-dataset-batch 661KB
make.bat 807B
CODEOWNERS 31B
constructs 614B
.coveragerc 107B
search_accessories.css 586B
pagination.css 267B
theme_overrides.css 225B
transform_input.csv 191KB
abalone-dataset.csv 187KB
sample_time_series.csv 148KB
data.csv 109KB
async-inference-pca-input.csv 96KB
customer_support.csv 32KB
classification_training_data.data.csv 23KB
CoLA.csv 21KB
baseline_dataset.csv 20KB
data.csv 19KB
iris_training.csv 19KB
features.csv 10KB
dataset.csv 8KB
sample.csv 7KB
baseline_dataset.csv 4KB
iris.csv 4KB
baseline_dataset.csv 2KB
batchtransform_test.csv 2KB
iris_training.csv 2KB
car-data.csv 2KB
iris_validation.csv 574B
iris_test.csv 573B
iris_test.csv 572B
dummy_data.csv 305B
iris_transform.csv 239B
train.csv 150B
data.csv 62B
valid_input.csv 27B
invalid_input.csv 25B
with_integers.csv 18B
dummy.csv 12B
dummy.csv 12B
data.csv 0B
data.csv 0B
variables.data-00000-of-00001 553B
variables.data-00000-of-00001 12B
variables.data-00000-of-00001 12B
.dictionary 302B
Dockerfile 2KB
Dockerfile 626B
dummy_tensor 311KB
first_10_rows_recordio 31KB
.flake8 183B
dummy_recipe.flow 1KB
foo 0B
.gitignore 514B
model.tar.gz 41.48MB
mnist.pkl.gz 15.42MB
images.gz 9.45MB
images.gz 1.57MB
model.tar.gz 399KB
model.tar.gz 142KB
tf-iris-model.tar.gz 133KB
model_mnist.tar.gz 129KB
packed_model.tar.gz 86KB
xgb_model.tar.gz 35KB
xgb_model.tar.gz 35KB
labels.gz 28KB
labels.gz 4KB
xgb_model.tar.gz 4KB
pytorch_mnist_source_code.tar.gz 3KB
tensorflow-serving-test-model.tar.gz 3KB
tensorflow_mnist_source_code.tar.gz 2KB
sourcedir.tar.gz 2KB
tensorflow_mnist_source_code_dummy.tar.gz 2KB
estimator_source_code_dummy1.tar.gz 2KB
sklearn-model.tar.gz 2KB
estimator_source_code_dummy2.tar.gz 1KB
mleap_model.tar.gz 1KB
sklearn-payload.tar.gz 1KB
mymodel-7B.tar.gz 382B
search.html 2KB
searchbox.html 1KB
MANIFEST.in 358B
variables.index 248B
variables.index 151B
variables.index 151B
tox.ini 5KB
mypy.ini 37B
notebook1_happypath.ipynb 15KB
step2_notebook.ipynb 14KB
simple.ipynb 13KB
sub.ipynb 2KB
TestJarFile.jar 2KB
HelloJavaSparkApp.jar 2KB
HelloJavaSparkApp.java 201B
model-artifacts.joblib 2KB
zidane.jpeg 165KB
zidane.jpeg 165KB
cat.jpg 114KB
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