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Showing posts with the label Keras
Change Loss Function Dynamically During Training In Keras, Without Recompiling Other Model Properties Like Optimizer

Change Loss Function Dynamically During Training In Keras, Without Recompiling Other Model Properties Like Optimizer

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Is it possible to set model.loss in a callback without re-compiling model.compile(...) after (since… Read more Change Loss Function Dynamically During Training In Keras, Without Recompiling Other Model Properties Like Optimizer
How To Load And Evaluate A Cnn Using A Test Set In Tensorflow?

How To Load And Evaluate A Cnn Using A Test Set In Tensorflow?

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I'm trying to train a CNN on a set of images. There are 2 folders: training_set and test_set, e… Read more How To Load And Evaluate A Cnn Using A Test Set In Tensorflow?
Converting Keras (tensorflow) Convolutional Neural Networks To Pytorch Convolutional Networks?

Converting Keras (tensorflow) Convolutional Neural Networks To Pytorch Convolutional Networks?

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Keras and PyTorch use different arguments for padding: Keras requires a string to be input, while P… Read more Converting Keras (tensorflow) Convolutional Neural Networks To Pytorch Convolutional Networks?
Neural Network Does Not Learn (loss Stays The Same)

Neural Network Does Not Learn (loss Stays The Same)

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My project partner and I are currently facing a problem in our latest university project. Our missi… Read more Neural Network Does Not Learn (loss Stays The Same)
Coverting Back One Hot Encoded Results Back To Single Column In Python

Coverting Back One Hot Encoded Results Back To Single Column In Python

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I was doing Multi-class Classification using Keras.It contained 5 classes of Output. I converted th… Read more Coverting Back One Hot Encoded Results Back To Single Column In Python
Balanced Error Rate As Metric Function

Balanced Error Rate As Metric Function

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I am trying to solve a binary classification problem with the sequential model from Keras and have … Read more Balanced Error Rate As Metric Function