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Keras_Sequential_API_Tutorial

Tutorial of sequential model of Keras

This tutorial contains:

  1. visualize image data (1. visualize_data.ipynb)

  2. training DNN (2. train_dnn_model.ipynb)

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  1. training CNN (3. train_cnn_model.ipynb)

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  1. training FCN (4. train_fcn_model.ipynb) Jonathan, Long, et al. "Fully convolutional networks for semantic segmentation." 2015.

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  1. training ResNet (5. train_res_model.ipynb) He, Kaiming, et al. "Deep residual learning for image recognition." 2015

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  1. design custom loss (6. train_custom_loss.ipynb)

  2. design custom optimizer (7. train_custom_optimizer.ipynb) Tim, Salimans, et al. "Weight normalization: a simple reparameterization to accelerate training of deep neural networks" 2016.

  3. design custom image preprocess function for training (8. train_custom_preprocess.ipynb) Terrance, DeVries, et al. "Improved regularization of convolutional neural networks with cutout" 2017.

If you can not view .ipynb file, please paste the link to jupyter nbviewer.

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Tutorial of sequential model of Keras

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