UCHIDA Masatoshi uchidama
uchidama
/ keras_mnist_simple_viewer.ipynb
Created
December 25, 2017 15:23
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uchidama
/ mnist_cnn_save_model.py
Created
December 28, 2017 07:37
A simple keras example code to save model.
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| '''Trains a simple convnet on the MNIST dataset. | |
| Gets to 99.25% test accuracy after 12 epochs | |
| (there is still a lot of margin for parameter tuning). | |
| 16 seconds per epoch on a GRID K520 GPU. | |
| ''' | |
| from __future__ import print_function | |
| import keras |
uchidama
/ keras_load_model_viewer.ipynb
Created
December 28, 2017 08:04
A simple example to predict mnist by load model on jupyter notebook
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uchidama
/ hand_write_digit_on_html_canvas_prediction.ipynb
Created
January 6, 2018 17:09
A digit that is written on HTML Canvas is predictted by a Conv model that learned MNIST. https://github.com/uchidama/HandWriteDigitOnHtmlCanvasPrediction
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uchidama
/ keras_cifar10_viewer.ipynb
Last active
January 16, 2018 00:57
CIFAR-10 pictures viewer using keras.
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uchidama
/ keras_cifar10_prediction.ipynb
Created
January 11, 2018 02:46
This code visualizes CIFAR-10 image files label prediction results by a ResNet model or a CNN model. https://github.com/uchidama/CIFAR10-Prediction-In-Keras
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uchidama
/ keras_fashion-mnist_simple_viewer.ipynb
Last active
August 15, 2019 18:37
Fashion mnist simple viewer in keras
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uchidama
/ keras_cifar100_viewer.ipynb
Created
January 16, 2018 02:17
CIFAR-100 pictures viewer using keras.
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uchidama
/ keras_fashion-mnist_prediction.ipynb
Last active
January 23, 2018 03:00
This code visualizes Fashion-MNIST image files label prediction results by a CNN model.
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uchidama
/ fashion-mnist_cnn_train.py
Last active
January 23, 2018 04:24
This code train fashion-mnist in Keras. Base code is https://github.com/keras-team/keras/blob/master/examples/mnist_cnn.py
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| '''Trains a simple convnet on the MNIST dataset. | |
| Gets to 99.25% test accuracy after 12 epochs | |
| (there is still a lot of margin for parameter tuning). | |
| 16 seconds per epoch on a GRID K520 GPU. | |
| ''' | |
| from __future__ import print_function | |
| import keras | |
| #from keras.datasets import mnist |
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