https://github.com/mostafa-wael/image-data-augmentation-with-keras
Data augmentation is a technique used to create more examples, artificially, from an existing dataset. This is useful if the dataset is small and we want to increase the number of examples. Data augmentation can often solve over-fitting so that our model generalizes well after training. For images, a variety of augmentation can be applied to increase the number of examples.
https://github.com/mostafa-wael/image-data-augmentation-with-keras
cnn dataaugmentation keras-tensorflow
Last synced: 2 months ago
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Data augmentation is a technique used to create more examples, artificially, from an existing dataset. This is useful if the dataset is small and we want to increase the number of examples. Data augmentation can often solve over-fitting so that our model generalizes well after training. For images, a variety of augmentation can be applied to increase the number of examples.
- Host: GitHub
- URL: https://github.com/mostafa-wael/image-data-augmentation-with-keras
- Owner: Mostafa-wael
- License: mit
- Created: 2020-09-28T05:36:54.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-10-06T02:14:19.000Z (over 4 years ago)
- Last Synced: 2025-01-22T12:45:53.162Z (4 months ago)
- Topics: cnn, dataaugmentation, keras-tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 1.01 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Image-Data-Augmentation-with-Keras
Data augmentation is a technique used to create more examples, artificially, from an existing dataset. This is useful if the dataset is small and we want to increase the number of examples. Data augmentation can often solve over-fitting so that our model generalizes well after training. For images, a variety of augmentation can be applied to increase the number of examples.
This is a guided project Offered By "Coursera Project Network".
Guided Project Link : https://www.coursera.org/projects/data-augmentation-keras