Deep Learning is an area of machine learning whose goal is to learn complex functions using special neural network architectures that are "deep" (consist of many layers).
I can't find how Keras defines "accuracy" and "loss". I know I can specify different metrics (e.g. mse, cross …
python tensorflow machine-learning deep-learning kerasWhat is the difference between categorical_accuracy and sparse_categorical_accuracy in Keras? There is no hint in the documentation …
python keras deep-learning neural-network classificationI'm a bit confused by the cross entropy loss in PyTorch. Considering this example: import torch import torch.nn as …
machine-learning deep-learning pytorch entropy lossHow train_on_batch() is different from fit()? What are the cases when we should use train_on_batch()?
machine-learning deep-learning kerasI am newbie in convolutional neural networks and just have idea about feature maps and how convolution is done on …
machine-learning computer-vision deep-learning conv-neural-network batch-normalizationI know that, in the 1D case, the convolution between two vectors, a and b, can be computed as conv(…
neural-network deep-learning conv-neural-network matrix-multiplication convolutionIn LSTM Network (Understanding LSTMs), Why input gate and output gate use tanh? what is the intuition behind this? it …
machine-learning deep-learning lstm recurrent-neural-network activation-functionThe introductory documentation, which I am reading (TOC here) uses the term "batch" (for instance here) without having defined it.
tensorflow machine-learning neural-network deep-learning tensorI am trying to grasp what TimeDistributed wrapper does in Keras. I get that TimeDistributed "applies a layer to every …
python machine-learning keras neural-network deep-learningI'm unittesting my Tensorflow code with nosetests but it produces such amount of verbose output that makes it useless. The …
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