Keras: Difference between revisions
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[https://keras.io/getting-started/faq/#how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore] |
[https://keras.io/getting-started/faq/#how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore] |
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=RNN= |
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[https://github.com/fchollet/keras/issues/3107 Dimension mismatch in LSTM] - Your input should be in this format (sequences, timesteps, dimensions). So based on your example, your input should be in (None, 8, 2). Your input now is (8,2). |
[https://github.com/fchollet/keras/issues/3107 Dimension mismatch in LSTM] - Your input should be in this format (sequences, timesteps, dimensions). So based on your example, your input should be in (None, 8, 2). Your input now is (8,2). |
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[http://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/ Time Series Prediction with LSTMs] |
[http://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/ Time Series Prediction with LSTMs] |
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=GANs= |
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[https://arxiv.org/abs/1701.00160 GANS] |
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Revision as of 10:41, 3 January 2017
Keras Callbacks how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore
RNN
Dimension mismatch in LSTM - Your input should be in this format (sequences, timesteps, dimensions). So based on your example, your input should be in (None, 8, 2). Your input now is (8,2).
Building Autoencoders in Keras - Includes LTSM!!!, Also shows a webserver graph showing progress. How to make a 2d graph. And how to interpolate between numbers...
Help: 'Wrong number of dimensions: expected 3, got 2 with shape (...)
cs231n-CNNs 10 - Recurrent Nerual Networks Lecture
Time Series Prediction with LSTMs