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)

3. training CNN (3. train_cnn_model.ipynb)

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

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

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

7. 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.

8. 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.

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