nateraw/aae-fraud-base-7
Updated
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15
Nate Raw PRO
nateraw
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Research interests
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models 32
nateraw/autoencoder-cifar10
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13
nateraw/baked-goods
Image Classification
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16
nateraw/baseball-stadium-foods
Image Classification
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20
nateraw/basic-ae-cifar10
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18
nateraw/bert-base-uncased-ag-news
Text Classification
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65
nateraw/bert-base-uncased-emotion
Text Classification
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Updated
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1,217
nateraw/bert-base-uncased-imdb
Text Classification
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148
nateraw/custom-featurizer
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5
nateraw/custom-sklearn-pipe-objects
Updated
nateraw/custom-torch-model
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6
nateraw/denver-nyc-paris
Image Classification
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15
nateraw/donut-or-bagel
Image Classification
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4
nateraw/dummy
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9
nateraw/food
Image Classification
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44
nateraw/hot-dog
Object Detection
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5
nateraw/iris-svc
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nateraw/pasta-pizza-ravioli
Image Classification
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84
nateraw/rare-puppers
Image Classification
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40
nateraw/resnet101
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7
nateraw/resnet152
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7
nateraw/resnet18
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6
nateraw/resnet34
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9
nateraw/resnet50
Image Classification
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24
nateraw/resnext101_32x8d
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8
nateraw/resnext50_32x4d
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5
nateraw/test_model_a
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2
nateraw/vit-age-classifier
Image Classification
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120
nateraw/vit-base-patch16-224-cifar10
Image Classification
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526
nateraw/vit-race-classifier
Image Classification
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37
nateraw/wide_resnet101_2
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7
nateraw/wide_resnet50_2
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5
datasets 9
nateraw/auto-cats-and-dogs
nateraw/auto-exp-2
nateraw/beans
Beans is a dataset of images of beans taken in the field using smartphone cameras. It consists of 3 classes: 2 disease classes and the healthy class. Diseases depicted include Angular Leaf Spot and Bean Rust. Data was annotated by experts from the National Crops Resources Research Institute (NaCRRI) in Uganda and collected by the Makerere AI res...