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Jupyter notebooks for the code samples of the book "Deep Learning with Python"

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I was evaluating whether these notebooks work with my AMD Radeon Pro 5700 XT. I have been able to get Keras models to use the GPU, however, the 'chapter07_working_with_keras' and...

I am implementing "Deep Dream" but got an error . code: `grads = K.gradients(loss,dream)[0]` Error : tf.gradients is not supported when eager execution is enabled. Use tf.GradientTape instead. I have...

The original codes in 7.1.2 are wrong. The parameters in Embedding lines are in the wrong order and now fixed.

The code below is causing an error. There seems to be a problem with batch_size. vae.fit(x=x_train, y=None, shuffle=True, epochs=10, batch_size=batch_size, validation_data=(x_test, None))

Hello! I try to use your generator for my case, where: lookback = 1440 = 5 days (timeframe = 5 minutes) step =1, i.e. my observations will be sampled at...

Why convolution is green when visualizing images? ![BXJ6U1AIIU5J}MNLI`PA@$P](https://user-images.githubusercontent.com/39075948/85196379-8a549580-b30c-11ea-98c6-b3a3f446a547.png)

Why the `batchsize = 32`, should it not be 20? Since the `steps_per_epoch = 100` and there is issue when using the generator in this way, since the `batchsize` is...

There is a problem in code number 13 where K.gradients is used it should be modified with tf.GradientTape

On running the cell under "Putting it all together: from raw text to word embeddings", the kernel throws the following error: UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position...