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Keras is a popular, open-source deep learning API for Python built on top of TensorFlow and is useful for fast implementation. Topics include efficient low-level tensor operations, computation of arbitrary gradients, scalable computations, export of graphs, etc.

3 votes
Accepted

Preprocessing and dropout in Autoencoders?

You should always normailze your input data, because the NN can learn faster with normalized data You can not generalize this questions, but in my experience, relu is better The use of dropout depend …
Lau's user avatar
  • 226
3 votes

Data augmentation based on the class type in the CNN model

I would not use data augmentation to only some classes. Maybe this brings a bias in your data set. I would use weighted examples. So if the network sees a class that has less example, the gradient i …
Lau's user avatar
  • 226