Network structure inspired by simplified models of biological neurons (brain cells).
I've noticed that a frequent occurrence during training is NANs being introduced. Often times it seems to be introduced by …
machine-learning neural-network deep-learning caffe gradient-descentI am using the TensorFlow backend. I am applying a convolution, max-pooling, flatten and a dense layer sequentially. The convolution …
tensorflow neural-network keras keras-layerI am looking for a method on how to calculate the number of layers and the number of neurons per …
machine-learning neural-network deep-learning artificial-intelligenceIs there a function call or another way to count the total number of parameters in a tensorflow model? By …
neural-network tensorflowI'm new to the topic of neural networks. I came across the two terms convolutional neural network and recurrent neural …
neural-network difference recurrent-neural-networkI've read about neural network a little while ago and I understand how an ANN (especially a multilayer perceptron that …
artificial-intelligence neural-networkI have tried the following code but didn't find the difference between np.dot and np.multiply with np.sum …
python numpy neural-network sum differenceWhat 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 classificationIn MNIST LSTM examples, I don't understand what "hidden layer" means. Is it the imaginary-layer formed when you represent an …
tensorflow neural-network lstm recurrent-neural-networkI am trying to create my own loss function: def custom_mse(y_true, y_pred): tmp = 10000000000 a = list(itertools.…
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